{"data":[{"id":"10.5880/fidgeo.2019.020","type":"dois","attributes":{"doi":"10.5880/fidgeo.2019.020","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, USA, US"}],"givenName":"Michele L.","familyName":"Cooke","name":"Cooke, Michele L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-4407-9676"}]},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, USA, US"}],"givenName":"Kevin","familyName":"Toenenboehn","name":"Toenenboehn, Kevin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-2307-7348"}]},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, USA, US"}],"givenName":"Jennifer","familyName":"Hatch","name":"Hatch, Jennifer","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0001-8877-2176"}]}],"titles":[{"lang":"en","title":"Digital Image Correlation data from oblique convergence experiments with wet kaolin"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://re3data.org/","name":"GFZ Data Services","lang":"en","publisherIdentifier":"https://doi.org/10.17616/R3VQ0S"},"container":{},"publicationYear":2019,"subjects":[{"subject":"oblique convergence","lang":"en"},{"subject":"analog experiments","lang":"en"},{"subject":"fault evolution","lang":"en"},{"subject":"slip partitioning","lang":"en"},{"subject":"EPOS","lang":"en"},{"subject":"multi-scale laboratories","lang":"en"},{"subject":"analogue models of geologic processes","lang":"en"},{"subject":"analogue modelling results","lang":"en"},{"subject":"software 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Software"},{"schemeUri":"https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords","subject":"EARTH SCIENCE \u003e SOLID EARTH \u003e TECTONICS \u003e PLATE TECTONICS \u003e FAULT MOVEMENT","valueUri":"https://gcmd.earthdata.nasa.gov/kms/concept/51ce7da1-b441-474f-b7e5-cedaa04903f7","lang":"en","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"schemeUri":"https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords","subject":"EARTH SCIENCE \u003e SOLID EARTH \u003e TECTONICS \u003e PLATE TECTONICS \u003e FAULT MOVEMENT \u003e FAULT MOVEMENT DIRECTION","valueUri":"https://gcmd.earthdata.nasa.gov/kms/concept/399e5858-8238-451f-8da3-84dc9edfe9a2","lang":"en","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"subject":"fault","valueUri":"http://inspire.ec.europa.eu/codelist/FaultTypeValue/fault","lang":"en","subjectScheme":"EPOS WP16 Analogue Geologic Structure"},{"subject":"fracture","valueUri":"http://epos/WP16Vocabulary/GeologicStructure/Fracture","lang":"en","subjectScheme":"EPOS WP16 Analogue Geologic Structure"},{"subject":"Matlab (Mathworks)","valueUri":"http://epos/WP16Vocabulary/Software/Matlab","lang":"en","subjectScheme":"EPOS WP16 Analogue Software"},{"subject":"Shear box","valueUri":"http://epos/WP16Vocabulary/Apparatus/Shear_box","lang":"en","subjectScheme":"EPOS WP16 Analogue Apparatus"},{"subject":"SLR camera","valueUri":"http://epos/WP16Vocabulary/Monitoring/SLR_camera","lang":"en","subjectScheme":"EPOS WP16 Analogue Monitoring"},{"subject":"Squeeze box","valueUri":"http://epos/WP16Vocabulary/Apparatus/Squeeze_box","lang":"en","subjectScheme":"EPOS WP16 Analogue Apparatus"},{"subject":"accretion","valueUri":"http://resource.geosciml.org/classifier/cgi/eventprocess/accretion","lang":"en","subjectScheme":"EPOS WP16 Analogue Process/Hazard"},{"subject":"transform faulting","valueUri":"http://resource.geosciml.org/classifier/cgi/eventprocess/transform_faulting","lang":"en","subjectScheme":"EPOS WP16 Analogue Process/Hazard"},{"subject":"active continental margin setting","valueUri":"http://resource.geosciml.org/classifier/cgi/eventenvironment/active_continental_margin_setting","lang":"en","subjectScheme":"EPOS WP16 Analogue Main Setting"},{"subject":"forearc setting","valueUri":"http://resource.geosciml.org/classifier/cgi/eventenvironment/forearc_setting","lang":"en","subjectScheme":"EPOS WP16 Analogue Main Setting"},{"subject":"subduction zone setting","valueUri":"http://resource.geosciml.org/classifier/cgi/eventenvironment/subduction_zone_setting","lang":"en","subjectScheme":"EPOS WP16 Analogue Main Setting"},{"subject":"transform plate boundary setting","valueUri":"http://resource.geosciml.org/classifier/cgi/eventenvironment/transform_plate_boundary_setting","lang":"en","subjectScheme":"EPOS WP16 Analogue Main Setting"},{"subject":"thrust 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L.","familyName":"Cooke","name":"Cooke, Michele L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-4407-9676"}],"contributorType":"ProjectLeader"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, USA, US"}],"givenName":"Kevin","familyName":"Toenenboehn","name":"Toenenboehn, Kevin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-2307-7348"}],"contributorType":"DataCollector"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, USA, US"}],"givenName":"Jennifer","familyName":"Hatch","name":"Hatch, Jennifer","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0001-8877-2176"}],"contributorType":"DataCollector"},{"nameType":"Organizational","affiliation":[{"name":"GFZ German Research Centre for Geosciences, Potsdam, Germany"}],"name":"HelTec-Helmholtz Laboratory for Tectonic Modelling (GFZ German Research Centre for Geosciences, Germany)","contributorType":"HostingInstitution","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Michele","familyName":"Cooke","name":"Cooke, 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International","lang":"en","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Experiments of oblique convergence at angles of 5, 10, 15, 20, 25 and 30 degrees from the margin within wet kaolin. One suite of experiments, denoted as ‘precut’, has a vertical surface precut within the clay with an electrified wire. The precut surface lies directly above the basal oblique dislocation. The other suite of experiments is ‘uncut’. Regardless of whether the experiments have a precut surface, slip partitioned fault systems, develop and persist in the experiments. Such systems have two simultaneously active faults with similar strike but different slip sense. Slip partitioning also develops regardless of whether the system first grows a reverse fault or strike slip fault in the experiment. The sequence and nature of strike-slip and reverse fault development depends on present of existing cut and convergence angle. \u003cbr\u003e\u003cbr\u003e This data set includes time series of incremental displacement maps for eleven experiments performed at the University of Massachusetts Amherst in January 2017 and March 2018 as well as animations of strain and uplift. The dataset includes the 30˚ convergence experiment with precut vertical surface but the 30˚ uncut experiment has not yet been performed. The time series data are organized into 11 netCDF files. The name of each file states the obliquity of convergence and whether the vertical surface was precut or not. \u003cbr\u003e\u003cbr\u003e Each netCDF file contains the following \u003cbr\u003e\u003cbr\u003e • ux = the incremental displacement field within the ROI (Region Of Interest) parallel to the margin (x-direction). The third dimension in the array corresponds to increment of deformation through the experiment. Units are mm. \u003cbr\u003e • uy = the incremental displacement field within the ROI perpendicular to the margin (y-direction). The third dimension in the array corresponds to increment of deformation through the experiment. Units are mm. \u003cbr\u003e • x = position parallel to the margin. Units are mm. \u003cbr\u003e • y = position perpendicular to the margin. Units are mm. \u003cbr\u003e\u003cbr\u003e The incremental displacements are calculated from DIC of photographs taken every 30 seconds using PIVlab (Thielicke, 2019). The net stepper motor speed is ~0.5 mm/min. \u003cbr\u003e\u003cbr\u003e The animations show strain evolution of all eleven experiments and uplift evolution of the 10 degree precut experiment. The strain evolution experiments overlay colormaps of incremental strain between successive photos on photographs of the experiment. Color saturation indicates the strain rate and hue indicates the slip vector. The uplift maps were made from stereovision analysis from pairs of photos. In most experiments, decorrelation of portions of the map prevented us from producing high quality uplift evolution animations from the start to the end of the experiment. Only the 10 degree convergence with precut vertical surface experiment had full coherence of uplift signal throughout the experiment and that animation."}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"EAR 1550133"}],"url":"https://dataservices.gfz.de/10.5880/fidgeo.2019.020/digital-image-correlation-data-from-oblique","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2020-02-09T16:03:46Z","registered":"2020-02-09T16:03:47Z","published":null,"updated":"2026-09-16T09:41:05Z"},"relationships":{"client":{"data":{"id":"tib.gfz","type":"clients"}}}},{"id":"10.5880/fidgeo.2018.021","type":"dois","attributes":{"doi":"10.5880/fidgeo.2018.021","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"University of Oslo"}],"givenName":"Jessica A.","familyName":"McBeck","name":"McBeck, Jessica A.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-4465-5522"}]},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst"}],"givenName":"Michele L.","familyName":"Cooke","name":"Cooke, Michele L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-4407-9676"}]},{"nameType":"Personal","affiliation":[{"name":"Université de Cergy-Pontoise"}],"givenName":"Pauline","familyName":"Souloumiac","name":"Souloumiac, Pauline","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-5370-0954"}]},{"nameType":"Personal","affiliation":[{"name":"Université de Cergy-Pontoise"}],"givenName":"Bertrand","familyName":"Maillot","name":"Maillot, Bertrand","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org/","nameIdentifier":"https://orcid.org/0000-0002-0495-8799"}]},{"nameType":"Personal","affiliation":[{"name":"Université de Cergy-Pontoise"}],"givenName":"Baptiste","familyName":"Mary","name":"Mary, Baptiste","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Supplement to: The influence of detachment strength on the evolving deformational energy budget of physical accretionary prisms"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://re3data.org/","name":"GFZ Data Services","lang":"en","publisherIdentifier":"https://doi.org/10.17616/R3VQ0S"},"container":{},"publicationYear":2018,"subjects":[{"subject":"work budget","lang":"en"},{"subject":"detachment strength","lang":"en"},{"subject":"frictional work","lang":"en"},{"subject":"off-fault deformation","lang":"en"},{"subject":"EPOS","lang":"en"},{"subject":"multi-scale laboratories","lang":"en"},{"subject":"analogue models of geologic processes","lang":"en"},{"subject":"analogue modelling results","lang":"en"},{"subject":"detachment fault","valueUri":"http://resource.geosciml.org/classifier/cgi/faulttype/detachment_fault","lang":"en","subjectScheme":"EPOS WP16 Analogue Geologic Structure"},{"schemeUri":"https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords","subject":"EARTH SCIENCE \u003e SOLID EARTH \u003e GEOMORPHIC LANDFORMS/PROCESSES \u003e TECTONIC PROCESSES","valueUri":"https://gcmd.earthdata.nasa.gov/kms/concept/f0bd7eeb-9004-4e40-a649-f6010d8a4303","lang":"en","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"schemeUri":"https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords","subject":"EARTH SCIENCE \u003e SOLID EARTH \u003e TECTONICS \u003e PLATE TECTONICS \u003e FAULT MOVEMENT","valueUri":"https://gcmd.earthdata.nasa.gov/kms/concept/51ce7da1-b441-474f-b7e5-cedaa04903f7","lang":"en","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"subject":"reverse fault","valueUri":"http://resource.geosciml.org/classifier/cgi/faulttype/reverse_fault","lang":"en","subjectScheme":"EPOS WP16 Analogue Geologic Structure"},{"subject":"Force sensor","valueUri":"http://epos/WP16Vocabulary/Monitoring/ForceSensor","lang":"en","subjectScheme":"EPOS WP16 Analogue Monitoring"},{"subject":"High frame rate camera","valueUri":"http://epos/WP16Vocabulary/Monitoring/HFR_camera","lang":"en","subjectScheme":"EPOS WP16 Analogue Monitoring"},{"subject":"Sand","valueUri":"http://epos/WP16Vocabulary/AnalogueMaterial/Sand","lang":"en","subjectScheme":"EPOS WP16 Analogue Material"},{"subject":"Sandbox (meter scale)","valueUri":"http://epos/WP16Vocabulary/Apparatus/Sandbox/Sandbox_m_scale","lang":"en","subjectScheme":"EPOS WP16 Analogue Apparatus"},{"subject":"accretion","valueUri":"http://resource.geosciml.org/classifier/cgi/eventprocess/accretion","lang":"en","subjectScheme":"EPOS WP16 Analogue 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Cergy-Pontoise"}],"givenName":"Baptiste","familyName":"Mary","name":"Mary, Baptiste","contributorType":"Researcher","nameIdentifiers":[]},{"nameType":"Organizational","affiliation":[{"name":"CNRS-Cergy-Pontoise University, Cergy-Pontoise, France"}],"name":"GECmodel-Laboratoire de modélisation analogique Géosciences et Environnement (CNRS-Cergy-Pontoise University, France )","contributorType":"HostingInstitution","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Oslo"}],"givenName":"Jessica","familyName":"McBeck","name":"McBeck, Jessica","contributorType":"ContactPerson","nameIdentifiers":[]}],"dates":[{"date":"2016-10","dateType":"Created"},{"date":"2018","dateType":"Issued"},{"date":"2018-10","dateType":"Valid"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.5194/se-9-1421-2018","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"1","rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","lang":"en","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Tracking the evolution of the deformational energy budget within accretionary systems provides insight into the driving mechanisms that control fault development. To quantify the impact of these mechanisms on overall system efficiency, we estimate energy budget components as the first thrust fault pair develops in dry-sand accretion analogue experiments. \u003cbr\u003e\u003cbr\u003e This data set includes photos taken and forces measured in four experiments performed at Université de Cergy-Pontoise in October-November 2016. The experiments are described in McBeck et al. (submitted). \u003cbr\u003e\u003cbr\u003e The data are organized into 5 main folders, with the following contents: \u003cbr\u003e 1) E373_photos: Contains 3 subfolders: droit_RDY, gauche_RDY, haut_RDY. Each subfolder contains images taken at 1 second intervals throughout experiment. droit_RDY, gauche_RDY, and haut_RDY contain photos of the right, left, and top of the sandpack. \u003cbr\u003e 2) E374_photos: Same organization and contents of folder E373_photos \u003cbr\u003e 3) E375_photos: Same organization and contents of folder E373_photos \u003cbr\u003e 4) E376_photos: Same organization and contents of folder E373_photos \u003cbr\u003e 5) forces: Contains text files that list the normal force against the backwall (N) and total applied normal displacement to the backwall (mm) in the second and first columns, respectively. The filename indicates which experiment the text file describes."}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982"},{"funderIdentifierType":"Crossref Funder ID","funderName":"American Association of Petroleum Geologists","funderIdentifier":"https://doi.org/10.13039/100009301"}],"url":"https://dataservices.gfz.de/10.5880/fidgeo.2018.021/supplement-to-the-influence-of-detachment","contentUrl":null,"metadataVersion":5,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-12-18T10:41:43Z","registered":"2018-12-18T10:41:44Z","published":null,"updated":"2026-09-16T09:40:53Z"},"relationships":{"client":{"data":{"id":"tib.gfz","type":"clients"}}}},{"id":"10.5880/fidgeo.2021.045","type":"dois","attributes":{"doi":"10.5880/fidgeo.2021.045","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Hanna M.","familyName":"Elston","name":"Elston, Hanna M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2420-5241"}]},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Michele","familyName":"Cooke","name":"Cooke, Michele","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4407-9676"}]}],"titles":[{"title":"Digital Image Correlation of evolving restraining bend experiments in wet kaolin"}],"publisher":{"name":"GFZ Data Services"},"container":{},"publicationYear":2022,"subjects":[{"subject":"restraining bend"},{"subject":"faulting"},{"subject":"strike-slip"},{"subject":"Digital Image Correlation"},{"subject":"wet kaolin clay"},{"subject":"EPOS"},{"subject":"multi-scale laboratories"},{"subject":"analogue models of geologic processes"},{"subject":"analogue modelling results"},{"subject":"EARTH SCIENCE \u0026gt; LAND SURFACE \u0026gt; GEOMORPHOLOGY \u0026gt; TECTONIC LANDFORMS/PROCESSES","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"subject":"EARTH SCIENCE \u0026gt; SOLID EARTH \u0026gt; TECTONICS \u0026gt; PLATE TECTONICS \u0026gt; FAULT MOVEMENT \u0026gt; FAULT MOVEMENT RATE","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"subject":"EARTH SCIENCE \u0026gt; SOLID EARTH \u0026gt; TECTONICS \u0026gt; PLATE TECTONICS \u0026gt; STRAIN","subjectScheme":"NASA/GCMD Earth Science Keywords"},{"subject":"EARTH SCIENCE SERVICES \u0026gt; MODELS \u0026gt; PHYSICAL/LABORATORY MODELS","subjectScheme":"NASA/GCMD Earth Science Keywords"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Hanna M.","familyName":"Elston","name":"Elston, Hanna M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2420-5241"}],"contributorType":"ContactPerson"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Hanna M.","familyName":"Elston","name":"Elston, Hanna M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2420-5241"}],"contributorType":"ProjectMember"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"givenName":"Michele","familyName":"Cooke","name":"Cooke, Michele","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4407-9676"}],"contributorType":"ProjectMember"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst, US"}],"name":"Geomechanics Physical Modeling Lab (University of Massachusetts Amherst, US)","nameIdentifiers":[],"contributorType":"HostingInstitution"},{"nameType":"Personal","affiliation":[{"name":"University of Massachusetts, Amherst"}],"givenName":"Hanna","familyName":"Elston","name":"Elston, Hanna","nameIdentifiers":[],"contributorType":"ContactPerson"}],"dates":[{"date":"2019-11-14","dateType":"Created"},{"date":"2022","dateType":"Issued"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1130/g49745.1","relatedIdentifierType":"DOI"},{"relationType":"Cites","relatedIdentifier":"10.1214/aoms/1177704472","relatedIdentifierType":"DOI"},{"relationType":"Cites","relatedIdentifier":"10.1214/aoms/1177728190","relatedIdentifierType":"DOI"},{"relationType":"Cites","relatedIdentifier":"10.5334/jors.bl","relatedIdentifierType":"DOI"},{"relationType":"Cites","relatedIdentifier":"10.3389/feart.2018.00152","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"We document the evolution of two 15° strike-slip restraining bends within wet kaolin. Computer-controlled stepper motors displace one half of the split-box apparatus at a constant rate of 0.5 mm/min to induce dextral faulting in a 2.5 cm thick layer of wet kaolin. The basal plate discontinuity has a 15° bend with a 2 cm stepover distance. Prior to any loading we cut a vertical fault surface that follows the basal plate discontinuity into the wet kaolin with an electrified probe and wooden template."}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"EAR 1550133"}],"url":"https://dataservices.gfz.de/10.5880/fidgeo.2021.045/digital-image-correlation-of-evolving-restraining","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2022-06-03T06:47:14Z","registered":"2022-06-03T06:47:15Z","published":null,"updated":"2026-09-01T07:23:22Z"},"relationships":{"client":{"data":{"id":"tib.gfz","type":"clients"}}}},{"id":"10.5523/bris.2vigq1fqc2o5e2bquvmr813oef","type":"dois","attributes":{"doi":"10.5523/bris.2vigq1fqc2o5e2bquvmr813oef","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[],"givenName":"Daniela","familyName":"Schmidt","name":"Schmidt, Daniela","nameIdentifiers":[{"nameIdentifierScheme":"URN","nameIdentifier":"http://data.bris.ac.uk/people/121054"}]}],"titles":[{"title":"Surviving rapid climate change in the deep sea during the Paleogene hyperthermals"},{"titleType":"AlternativeTitle","title":"Foster et al 2013"}],"publisher":{"name":"University of Bristol"},"container":{},"publicationYear":2026,"subjects":[],"contributors":[],"dates":[{"date":"2026","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA"},"relatedIdentifiers":[{"relationType":"IsCitedBy","relatedIdentifier":"https://doi.org/10.1073/pnas.1300579110","relatedIdentifierType":"URN"}],"relatedItems":[],"sizes":[],"formats":["text/plain; charset=UTF-8","application/octet-stream","application/zip"],"version":null,"rightsList":[],"descriptions":[{"descriptionType":"Abstract","description":"This dataset contains SRXTM (Synchrotron X-ray Tomographic Microscopy) images, taken using the TOMCAT beamline tomography station at the Swiss Light Source, Paul Scherrer Institut, Villigen, Switzerland, for N. truempyi (9) and O.umbonatus (35). \n\nThe data accompanies the following paper: Foster, L.C., Schmidt, D.N., Thomas, E., Arndt, S. and Ridgwell, A., 2013. Surviving rapid climate change in the deep sea during the Paleogene hyperthermals. Proceedings of the National Academy of Sciences, 110(23), pp.9273-9276.\n\n################################################\nSummary of the data provided for each specimen:\n\nFor all specimens (n = 44): a 2D tif stack of the reconstructed tomographic slice data; Avizo labels (.am) containing segmentation information, and a .txt document detailing scan settings.\n\nRaw tomographic data for each specimen consists of zipped archives containing a stacked series of 2D 8-bit TIF files that represent maps of X-ray attenuation. The individual slices can be viewed with standard graphics software. \nThe datasets can be studied in 3D using tomographic reconstruction software such as Avizo (www.avizo3d.com)\nWorking files consist of Avizo files (.am files), which can be opened in Avizo (www.avizo3d.com/).\n\nAlso see dataset: Schmidt, D., Shi, Y. (2026): Morphological Plasticity in Benthic Foraminifera during Paleogene Warming Events. https://doi.org/10.5523/bris.37hp1fmid92ue2pe234hbpmezk."}],"geoLocations":[],"fundingReferences":[{"funderName":"Swiss Light Source","awardNumber":"20090840."},{"funderIdentifierType":"Crossref Funder ID","funderName":"Leverhulme Trust","funderIdentifier":"https://doi.org/10.13039/501100000275"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Royal Society","funderIdentifier":"https://doi.org/10.13039/501100000288"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"OCE 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Xinye","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1764-1141"}],"affiliation":[]},{"nameType":"Personal","givenName":"Farhanaz","familyName":"Farheen","name":"Farheen, Farhanaz","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0009-0006-5683-6853"}],"affiliation":[]},{"nameType":"Personal","givenName":"Daisuke","familyName":"Kihara","name":"Kihara, Daisuke","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4091-6614"}],"affiliation":[]},{"nameType":"Personal","givenName":"Hong","familyName":"Zhou","name":"Zhou, Hong","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8373-4717"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2025,"subjects":[{"subject":"Workflow","lang":"en-US"},{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Software","lang":"en-US"},{"subject":"workflow","lang":"en-US"},{"subject":"dataset generation","lang":"en-US"},{"subject":"deep learning","lang":"en-US"}],"contributors":[],"dates":[{"date":"2025-10-14","dateType":"Available"},{"date":"2025","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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AI-driven structural biology. As deep learning models become increasingly central to atomic structure modeling, researchers face significant challenges in assembling high-quality training data. Existing workflows are often manual, inconsistent, and lack standardized quality control, resulting in time-consuming data preparation and variable dataset quality. CryoDataBot aims to fill this gap by providing an automated, modular pipeline that simplifies dataset construction and supports diverse modeling objectives.\u003cbr\u003eThe pipeline integrates key steps such as cryoEM map retrieval, voxel resampling, structural labeling, and subvolume partitioning. It also offers fine-grained quality control features, including residue-level similarity filtering, Q-score thresholds, and mapmodel fitness evaluation (MMF), which together help eliminate redundant or low-quality entries. Users can configure these parameters through a graphical interface to generate task-specific datasets, while intermediate outputs are retained to support reproducibility and debugging.\u003cbr\u003eThis workflow enables researchers to efficiently construct high-quality datasets tailored to the specific requirements of their AI models. It supports training and fine-tuning of deep learning architectures, and provides a reproducible framework for building task-specific cryoEM datasets. By offering flexible resolution support and standardized formatting, CryoDataBot helps streamline model development and promotes consistent data preparation practices in AI-driven structural biology.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Institutes of Health","awardNumber":"R01GM071940"},{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Institutes of Health","awardNumber":"R01GM133840"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IIS2211598"}],"url":"http://gigadb.org/dataset/102765","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2025-10-14T07:59:35Z","registered":"2025-10-14T07:59:36Z","published":null,"updated":"2025-10-14T07:59:36Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100384","type":"dois","attributes":{"doi":"10.5524/100384","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Hongyang","familyName":"Li","name":"Li, Hongyang","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7902-4157"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bharat","familyName":"Panwar","name":"Panwar, Bharat","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gilbert, S.","familyName":"Omenn","name":"Omenn, Gilbert, S.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8976-6074"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yuanfang","familyName":"Guan","name":"Guan, Yuanfang","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8275-2852"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Accurate Prediction of Personalized Olfactory Perception from Large-Scale Chemoinformatic Features\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2017,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"olfactory perception","lang":"en-US"},{"subject":"structure-odor relationships","lang":"en-US"},{"subject":"random forest","lang":"en-US"},{"subject":"chemoinformatics","lang":"en-US"}],"contributors":[],"dates":[{"date":"2017-12-20","dateType":"Available"},{"date":"2017","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/gix127","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/Hongyang449/olfaction_prediction_manuscript","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://www.synapse.org/#!Synapse:syn3098005","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["119.5 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in DREAM Olfaction Prediction Challenge.\u003cbr\u003e\r\n\r\nWe find that random forest model consisting of multiple decision trees is well-suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and non-degenerative features is sufficient for accurate prediction. \r\n\r\n\u003cbr\u003e\r\nOur random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1452656"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Alzheimer’s Association","awardNumber":"BAND-15-367116"}],"url":"http://gigadb.org/dataset/100384","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2017-12-20T09:56:32Z","registered":"2017-12-20T09:56:34Z","published":null,"updated":"2025-07-22T12:11:24Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100422","type":"dois","attributes":{"doi":"10.5524/100422","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Kirill","familyName":"Grigorev","name":"Grigorev, Kirill","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sergey","familyName":"Kliver","name":"Kliver, Sergey","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Pavel","familyName":"Dobrynin","name":"Dobrynin, Pavel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Aleksey","familyName":"Komissarov","name":"Komissarov, Aleksey","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Walter","familyName":"Wolfsberger","name":"Wolfsberger, Walter","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ksenia","familyName":"Krasheninnikova","name":"Krasheninnikova, Ksenia","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yashira, M.","familyName":"Afanador-Hernández","name":"Afanador-Hernández, Yashira, M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Adam, L.","familyName":"Brandt","name":"Brandt, Adam, L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Liz, A.","familyName":"Paulino","name":"Paulino, Liz, A.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rosanna","familyName":"Carreras","name":"Carreras, Rosanna","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Luis, E.","familyName":"Rodríguez","name":"Rodríguez, Luis, E.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Adrell","familyName":"Núñez","name":"Núñez, Adrell","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jessica, R.","familyName":"Brandt","name":"Brandt, Jessica, R.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Filipe","familyName":"Silva","name":"Silva, Filipe","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"J., David","familyName":"Hernández-Martich","name":"Hernández-Martich, J., David","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Audrey, J.","familyName":"Majeske","name":"Majeske, Audrey, J.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Agostinho","familyName":"Antunes","name":"Antunes, Agostinho","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alfred, L.","familyName":"Roca","name":"Roca, Alfred, L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9217-5593"}],"affiliation":[]},{"nameType":"Personal","givenName":"Stephen, J","familyName":"O’Brien","name":"O’Brien, Stephen, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7353-8301"}],"affiliation":[]},{"nameType":"Personal","givenName":"Juan, Carlos","familyName":"Martínez-Cruzado","name":"Martínez-Cruzado, Juan, Carlos","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Taras, K.","familyName":"Oleksyk","name":"Oleksyk, Taras, K.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Innovative assembly strategy contributes to understanding the evolution and conservation genetics of the endangered Solenodon paradoxus from the island of Hispaniola\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience 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Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giy025","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"https://www.ebi.ac.uk/ena/browser/view/NKTL01000000","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject?term=PRJNA368679","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://doi.org/10.5281/zenodo.1185377","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1.34 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Solenodons are insectivores living in Hispaniola and Cuba that form an isolated branch in the tree of placental mammals highly divergent from other eulipothyplan insectivores The history, unique biology and adaptations of these enigmatic venomous species could be illuminated by the availability of genome data, but a whole genome assembly for solenodons has not been previously performed, partially due to the difficulty in obtaining samples from the field. \u003cbr\u003eIsland isolation and reduced numbers have likely resulted in high homozygosity within the Hispaniolan solenodon (\u003ci\u003eSolenodon paradoxus\u003c/i\u003e), thus we tested the performance of several assembly strategies on the genome of this genetically impoverished species. The string-graph based assembly strategy seemed a better choice compared to the conventional de Bruijn graph approach, due to the high levels of homozygosity, which is often a hallmark of endemic or endangered species. \u003cbr\u003eA consensus reference genome was assembled from sequences of five individuals from the southern subspecies (\u003ci\u003eS. p. woodi\u003c/i\u003e). In addition, we obtained additional sequence from one sample of the northern subspecies (\u003ci\u003eS. p. paradoxus\u003c/i\u003e). The resulting genome assemblies were compared to each other, and annotated for genes, with a specific emphasis on venom genes, repeats, variable microsatellite loci and other genomic variants. Phylogenetic positioning and selection signatures were inferred based on 4,416 single copy orthologs from 10 other mammals. We estimated that solenodons diverged from other extant mammals 73.6 Mya. Patterns of SNP variation allowed us to infer population demography, which supported a subspecies split within the Hispaniolan solenodon at least 300 Kya.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1432092"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Ministry of Education and Science of the Russian Federation","funderIdentifier":"https://doi.org/10.13039/501100003443","awardNumber":"Mega-grant 11.G34.31.0068"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Saint Petersburg State University","funderIdentifier":"https://doi.org/10.13039/501100004285","awardNumber":"1.50.1623.2013"}],"url":"http://gigadb.org/dataset/100422","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-03-09T14:47:39Z","registered":"2018-03-09T14:47:40Z","published":null,"updated":"2025-05-26T17:20:52Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100434","type":"dois","attributes":{"doi":"10.5524/100434","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Kingshuk","familyName":"Mukherjee","name":"Mukherjee, Kingshuk","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1647-8741"}],"affiliation":[]},{"nameType":"Personal","givenName":"Darshan","familyName":"Washimkar","name":"Washimkar, Darshan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1862-8790"}],"affiliation":[]},{"nameType":"Personal","givenName":"Martin","familyName":"Muggli","name":"Muggli, Martin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9283-0049"}],"affiliation":[]},{"nameType":"Personal","givenName":"Leena","familyName":"Salmela","name":"Salmela, Leena","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0756-543X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Christina","familyName":"Boucher","name":"Boucher, Christina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9509-9725"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Error Correcting Optical Mapping Data\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2018,"subjects":[{"subject":"Imaging","lang":"en-US"},{"subject":"Genomic","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"optical mapping","lang":"en-US"},{"subject":"error correction","lang":"en-US"}],"contributors":[],"dates":[{"date":"2018-05-01","dateType":"Available"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giy061","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/kingufl/cOMet","relatedIdentifierType":"URL"},{"relationType":"Cites","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"},{"relationType":"Cites","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["12.06 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Optical mapping is a unique system that is capable of producing high-resolution, high-throughput genomic map data that gives information about the structure of a genome. Recently it has been used for scaffolding contigs and assembly validation for large-scale sequencing projects, including the maize, goat, and amborella genomes. However, a major impediment in the use of this data is the variety and quantity of errors in the raw optical mapping data, which are called Rmaps. The challenges associated with using Rmap dataand thus, optical mapping datais analogous to dealing with insertions and deletions in the alignment of long reads. Moreover, they are arguably harder to tackle since the data is integral and susceptible to inaccuracy. We develop cOMet to error correct Rmap data, which to the best of our knowledge is the only optical mapping error correction method. Our experimental results demonstrate that cOMet corrects 82.49% of insertion errors and 77.38% of deletion errors in Rmap data generated from the E. coli K-12 reference genome. Out of the deletion errors corrected, 98.26% are true errors. Similarly, out of the insertion errors corrected, 82.19% are true errors. It also successfully scales to large genomes, improving the quality of 78% and 99% of the Rmaps in the plum and goat genomes, respectively. Lastly, we show the utility of error correction by demonstrating how it improves the assembly of Rmap data. Error corrected Rmap data results in an assembly that is more contiguous, and covers a larger fraction of the genome.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Academy of Finland","awardNumber":"284598"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1618814"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Academy of Finland","awardNumber":"308030"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Academy of Finland","awardNumber":"314170"}],"url":"http://gigadb.org/dataset/100434","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-05-01T17:01:38Z","registered":"2018-05-01T17:01:39Z","published":null,"updated":"2025-05-26T17:20:49Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100655","type":"dois","attributes":{"doi":"10.5524/100655","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Glaucia, Mendes","familyName":"Souza","name":"Souza, Glaucia, Mendes","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6903-9913"}],"affiliation":[]},{"nameType":"Personal","givenName":"Marie-Anne, Van","familyName":"Van Sluys","name":"Van Sluys, Marie-Anne, Van","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6506-2734"}],"affiliation":[]},{"nameType":"Personal","givenName":"Carolina, Gimiliani","familyName":"Lembke","name":"Lembke, Carolina, Gimiliani","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0653-2353"}],"affiliation":[]},{"nameType":"Personal","givenName":"Hayan","familyName":"Lee","name":"Lee, Hayan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0571-3192"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gabriel","familyName":"Rodrigues Alves Margarido","name":"Rodrigues Alves Margarido, Gabriel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2327-0201"}],"affiliation":[]},{"nameType":"Personal","givenName":"Carlos, Takeshi","familyName":"Hotta","name":"Hotta, Carlos, Takeshi","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3349-6121"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jonas, Weissmann","familyName":"Gaiarsa","name":"Gaiarsa, Jonas, Weissmann","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5073-5895"}],"affiliation":[]},{"nameType":"Personal","givenName":"Augusto, Lima","familyName":"Diniz","name":"Diniz, Augusto, Lima","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0407-1039"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mauro, Medeiros","familyName":"Oliveira","name":"Oliveira, Mauro, Medeiros","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2048-6664"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sávio, Siqueira","familyName":"Ferreira","name":"Ferreira, Sávio, Siqueira","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9926-9066"}],"affiliation":[]},{"nameType":"Personal","givenName":"Milton, Yutaka","familyName":"Nishiyama-Jr","name":"Nishiyama-Jr, Milton, Yutaka","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2410-0562"}],"affiliation":[]},{"nameType":"Personal","givenName":"Felipe","familyName":"ten-Caten","name":"ten-Caten, Felipe","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7771-1490"}],"affiliation":[]},{"nameType":"Personal","givenName":"Geovani, Tolfo","familyName":"Ragagnin","name":"Ragagnin, Geovani, Tolfo","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Pablo, de","familyName":"Morais Andrade","name":"Morais Andrade, Pablo, de","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3177-5330"}],"affiliation":[]},{"nameType":"Personal","givenName":"Robson, Francisco","familyName":"de Souza","name":"de Souza, Robson, Francisco","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5284-4630"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gianlucca, Gonçalves","familyName":"Nicastro","name":"Nicastro, Gianlucca, Gonçalves","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3133-2441"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ravi","familyName":"Pandya","name":"Pandya, Ravi","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0258-4604"}],"affiliation":[]},{"nameType":"Personal","givenName":"Changsoo","familyName":"Kim","name":"Kim, Changsoo","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3596-2934"}],"affiliation":[]},{"nameType":"Personal","givenName":"Hui","familyName":"Guo","name":"Guo, Hui","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alan, Mitchell","familyName":"Durham","name":"Durham, Alan, Mitchell","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9846-6911"}],"affiliation":[]},{"nameType":"Personal","givenName":"Monalisa, Sampaio","familyName":"Carneiro","name":"Carneiro, Monalisa, Sampaio","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9835-7205"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jisen","familyName":"Zhang","name":"Zhang, Jisen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xingtan","familyName":"Zhang","name":"Zhang, Xingtan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Qing","familyName":"Zhang","name":"Zhang, Qing","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ray","familyName":"Ming","name":"Ming, Ray","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9417-5789"}],"affiliation":[]},{"nameType":"Personal","givenName":"Michael, C","familyName":"Schatz","name":"Schatz, Michael, C","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4118-4446"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bob","familyName":"Davidson","name":"Davidson, Bob","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1672-8421"}],"affiliation":[]},{"nameType":"Personal","givenName":"Andrew, H","familyName":"Paterson","name":"Paterson, Andrew, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2159-0487"}],"affiliation":[]},{"nameType":"Personal","givenName":"David","familyName":"Heckerman","name":"Heckerman, David","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4274-6084"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Assembly of the 373K gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world’s leading biomass crop\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"allele","lang":"en-US"},{"subject":"bioenergy","lang":"en-US"},{"subject":"biomass","lang":"en-US"},{"subject":"genome","lang":"en-US"},{"subject":"polyploid","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-10-16","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz129","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA431722","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE124990","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://sucest-fun.org/cgi-bin/cane_regnet/gbrowse2/gbrowse/microsoft_genome_moleculo_scga7/","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/sp80-3280-genome","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["2 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10-13 sets of chromosomes from two Saccharum species. The ploidy, hybridity and size of the genome, estimated to have in excess of 10 Gb, pose a great challenge for sequencing.\u003cbr\u003e Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes, indicates that we could resolve 2-6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions and gene promoter analysis shows differences in regulatory elements within gene families and are species-specific expressed. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), two gene families central to carbon partitioning. SP80-3280 have particular regulatory elements involved in sucrose synthesis not found in the ancestor \u003ci\u003eS. spontaneum\u003c/i\u003e. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison to sorghum reveals predominantly biallelic variations in sugarcane, consistent with the formation of two subgenomes after their divergence ca. 3.8~4.6 MYA and reveals SNVs that may underlie their differences. \u003cbr\u003e This assembly represents a large step towards a whole genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2012/51062-3"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2008/52146-0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2014/50921-8"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1350041"},{"funderIdentifierType":"Crossref Funder 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Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2015/22993-7"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Brazilian National Council for Scientific and Technological Development","awardNumber":"159094/2014-3"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2015/15346-5"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2013/18322-4"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2017/02270-6"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2013/23048-9\r\n"},{"funderIdentifierType":"Crossref Funder ID","funderName":"CAPES","awardNumber":"DS-1454337"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2016/06917-1"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2013/07467-1"},{"funderIdentifierType":"Crossref Funder ID","funderName":"São Paulo Research Foundation","funderIdentifier":"https://doi.org/10.13039/501100001807","awardNumber":"grant #2017/02842-0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Brazilian National Council for Scientific and Technological Development","awardNumber":"309566/2015-0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Health","awardNumber":"R01-HG006677"}],"url":"http://gigadb.org/dataset/100655","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-10-16T13:08:15Z","registered":"2019-10-16T13:08:16Z","published":null,"updated":"2025-05-26T17:20:48Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100514","type":"dois","attributes":{"doi":"10.5524/100514","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Jakub","familyName":"Pospíšil","name":"Pospíšil, Jakub","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3615-5752"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tomáš","familyName":"Lukeš","name":"Lukeš, Tomáš","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Justin","familyName":"Bendesky","name":"Bendesky, Justin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Karel","familyName":"Fliegel","name":"Fliegel, Karel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5737-6736"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kathrin","familyName":"Spendier","name":"Spendier, Kathrin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Guy, M","familyName":"Hagen","name":"Hagen, Guy, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4802-9481"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2018,"subjects":[{"subject":"Imaging","lang":"en-US"},{"subject":"structured illumination microscopy","lang":"en-US"},{"subject":"simtoolbox","lang":"en-US"},{"subject":"fluorescence","lang":"en-US"},{"subject":"sim","lang":"en-US"},{"subject":"super-resolution microscopy","lang":"en-US"},{"subject":"bayesian methods","lang":"en-US"},{"subject":"live cell imaging","lang":"en-US"}],"contributors":[],"dates":[{"date":"2018-10-10","dateType":"Available"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giy126","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://mmtg.fel.cvut.cz/SIMToolbox/","relatedIdentifierType":"URL"},{"relationType":"Cites","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["11.27 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods, and with newer Bayesian restoration approaches which we are developing. Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments is not typically published. Publically available, high quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data was processed with SIMToolbox, an open source and freely available software solution for SIM.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"1R15GM128166-01"},{"funderIdentifierType":"Crossref Funder ID","funderName":"SCIEX","funderIdentifier":"https://doi.org/10.13039/100010534","awardNumber":"13.183"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1727033"},{"funderIdentifierType":"Crossref Funder ID","funderName":"České Vysoké Učení Technické v Praze","awardNumber":"SGS18/141/OHK3/2T/13"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Czech Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100001824","awardNumber":"GA17-05840S"}],"url":"http://gigadb.org/dataset/100514","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-10-12T07:09:18Z","registered":"2018-10-12T07:09:19Z","published":null,"updated":"2025-05-26T17:20:41Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100722","type":"dois","attributes":{"doi":"10.5524/100722","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Benjamin, B","familyName":"Chu","name":"Chu, Benjamin, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8342-2361"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kevin, L","familyName":"Keys","name":"Keys, Kevin, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4886-6666"}],"affiliation":[]},{"nameType":"Personal","givenName":"Christopher, A","familyName":"German","name":"German, Christopher, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2717-5316"}],"affiliation":[]},{"nameType":"Personal","givenName":"Hua","familyName":"Zhou","name":"Zhou, Hua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1320-7118"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jin, J","familyName":"Zhou","name":"Zhou, Jin, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7983-0274"}],"affiliation":[]},{"nameType":"Personal","givenName":"Eric, M","familyName":"Sobel","name":"Sobel, Eric, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1718-0031"}],"affiliation":[]},{"nameType":"Personal","givenName":"Janet, S","familyName":"Sinsheimer","name":"Sinsheimer, Janet, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9540-5956"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kenneth","familyName":"Lange","name":"Lange, Kenneth","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1313-5030"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Iterative Hard Thresholding in GWAS: Generalized Linear Models, Prior Weights, and Double Sparsity\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2020,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"gwas","lang":"en-US"},{"subject":"multiple regression","lang":"en-US"},{"subject":"high dimensional inference","lang":"en-US"},{"subject":"iterative hard thresholding","lang":"en-US"},{"subject":"biobank","lang":"en-US"}],"contributors":[],"dates":[{"date":"2020-04-08","dateType":"Available"},{"date":"2020","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giaa044","relatedIdentifierType":"DOI"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/OpenMendel/MendelIHT.jl","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["33 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Consecutive testing of single nucleotide polymorphisms (SNPs) is usually employed to identify genetic variants associated with complex traits. Ideally one should model all covariates in unison, but most existing analysis methods for genome-wide association studies (GWAS) perform only univariate regression. \u003cbr\u003eWe extend and efficiently implement iterative hard thresholding (IHT) for multiple regression, treating all SNPs simultaneously. Our extensions accommodate generalized linear models (GLMs), prior information on genetic variants, and grouping of variants. In our simulations, IHT recovers up to 30% more true predictors than SNP-by-SNP association testing, and exhibits a 2 to 3 orders of magnitude decrease in false positive rates compared to lasso regression. We also test IHT on the UK Biobank hypertension phenotypes and the Northern Finland Birth Cohort of 1966 cardiovascular phenotypes. We find that IHT scales to the large datasets of contemporary human genetics and recovers the plausible genetic variants identified by previous studies. \u003cbr\u003e Our real data analysis and simulation studies suggest that IHT can (a) recover highly correlated predictors, (b) avoid over-fitting, (c) deliver better true positive and false positive rates than either marginal testing or lasso regression, (d) recover unbiased regression coefficients, (e) exploit prior information and group-sparsity and (f) be used with biobank sized data sets. Although these advances are studied for GWAS inference, our extensions are pertinent to other regression problems with large numbers of predictors.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Health","awardNumber":"NIH T32-HG002536"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Google","funderIdentifier":"https://doi.org/10.13039/100006785"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Heart and Lung Institute","funderIdentifier":"https://doi.org/10.13039/501100000850","awardNumber":"R01HL135156"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Gordon and Betty More Foundation","awardNumber":"GBMF3834"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Alfred P. Sloan Foundation","funderIdentifier":"https://doi.org/10.13039/100000879","awardNumber":"2013-10-27"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Human Genome Research Institute","funderIdentifier":"https://doi.org/10.13039/100000051","awardNumber":"HG006139"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Human Genome Research Institute","funderIdentifier":"https://doi.org/10.13039/100000051","awardNumber":"HG006139"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of General Medical Sciences","funderIdentifier":"https://doi.org/10.13039/100000057","awardNumber":"GM053275"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of General Medical Sciences","funderIdentifier":"https://doi.org/10.13039/100000057","awardNumber":"GM053275"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of General Medical Sciences","funderIdentifier":"https://doi.org/10.13039/100000057","awardNumber":"GM053275"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Human Genome Research Institute","funderIdentifier":"https://doi.org/10.13039/100000051","awardNumber":"HG009120"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DMS1264153"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Burroughs Wellcome Fund","funderIdentifier":"https://doi.org/10.13039/100000861"}],"url":"http://gigadb.org/dataset/100722","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2020-04-08T10:17:59Z","registered":"2020-04-08T10:18:02Z","published":null,"updated":"2025-05-26T17:20:35Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100523","type":"dois","attributes":{"doi":"10.5524/100523","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Venice","familyName":"Juanillas","name":"Juanillas, Venice","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7581-5501"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alexis","familyName":"Dereeper","name":"Dereeper, Alexis","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8120-8409"}],"affiliation":[]},{"nameType":"Personal","givenName":"Nicolas","familyName":"Beaume","name":"Beaume, Nicolas","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7518-7277"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gaetan","familyName":"Droc","name":"Droc, Gaetan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1849-1269"}],"affiliation":[]},{"nameType":"Personal","givenName":"Joshua","familyName":"Dizon","name":"Dizon, Joshua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"John, Robert","familyName":"Mendoza","name":"Mendoza, John, Robert","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3131-1149"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jon, Peter","familyName":"Perdon","name":"Perdon, Jon, Peter","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Locedie","familyName":"Mansueto","name":"Mansueto, Locedie","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Lindsay","familyName":"Triplett","name":"Triplett, Lindsay","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5560-9257"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jillian","familyName":"Lang","name":"Lang, Jillian","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8890-7026"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gabriel","familyName":"Zhou","name":"Zhou, Gabriel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kunalan","familyName":"Ratharanjan","name":"Ratharanjan, Kunalan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7749-2627"}],"affiliation":[]},{"nameType":"Personal","givenName":"Beth","familyName":"Plale","name":"Plale, Beth","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2164-8132"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jason","familyName":"Haga","name":"Haga, Jason","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6407-0003"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jan, E","familyName":"Leach","name":"Leach, Jan, E","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7252-4397"}],"affiliation":[]},{"nameType":"Personal","givenName":"Manuel","familyName":"Ruiz","name":"Ruiz, Manuel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Michael","familyName":"Thomson","name":"Thomson, Michael","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Nickolai","familyName":"Alexandrov","name":"Alexandrov, Nickolai","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3381-0918"}],"affiliation":[]},{"nameType":"Personal","givenName":"Pierre","familyName":"Larmande","name":"Larmande, Pierre","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2923-9790"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tobias","familyName":"Kretzschmar","name":"Kretzschmar, Tobias","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8227-0746"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ramil, P","familyName":"Mauleon","name":"Mauleon, Ramil, P","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8512-144X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Rice Galaxy: an open resource for plant science\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{"identifier":"http://iric.irri.org/resources/3000-genomes-project","identifierType":"URL","type":"DataRepository"},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"rice","lang":"en-US"},{"subject":"breeding","lang":"en-US"},{"subject":"workflow","lang":"en-US"},{"subject":"genomes","lang":"en-US"},{"subject":"high-density genotypes","lang":"en-US"},{"subject":"reproducibility","lang":"en-US"},{"subject":"snp","lang":"en-US"},{"subject":"gwas","lang":"en-US"},{"subject":"galaxy project","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-01-03","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz028","relatedIdentifierType":"DOI"},{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz156","relatedIdentifierType":"DOI"},{"relationType":"IsPartOf","resourceTypeGeneral":"Project","relatedIdentifier":"http://iric.irri.org/resources/3000-genomes-project","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://galaxy.irri.org","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://aws.amazon.com/public-datasets/3000-rice-genome/","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/InternationalRiceResearchInstitute/RiceGalaxy","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/bgruening/docker-galaxy-stable","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/Data-to-Insight-Center/RDA-PRAGMA-Data-Service/wiki/Welcome-to-PRAGMA-Data-Service-Prototype","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://github.com/SouthGreenPlatform/Uniqprimer","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://iric.irri.org/resources/3000-genomes-project","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://snp-seek.irri.org/_download.zul","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://13.250.174.27:8080/library/list#folders/Fc7f77e5e366c2645","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://galaxytoolshed.excellenceinbreeding.org/","relatedIdentifierType":"URL"},{"relationType":"Cites","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["201.86 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci (QTL) discovery and molecular marker development. Comparative sequence analyses across QTL regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers. We adopted the Galaxy framework to build the federated Rice Galaxy resource, with shared datasets, tools, and analysis workflows relevant to rice research. The shared datasets include high density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from nine published rice genomes. Rice Galaxy includes tools for designing single nucleotide polymorphism (SNP) assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented. Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"PRAGMA grant number:NSF OCI 1234983"},{"funderIdentifierType":"Crossref Funder ID","funderName":"MacArthur Foundation"},{"funderIdentifierType":"Crossref Funder ID","funderName":"AIST"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Taiwan Council of Agriculture Grant"},{"funderIdentifierType":"Crossref Funder ID","funderName":"CGIAR Excellence in Breeding Platform"}],"url":"http://gigadb.org/dataset/100523","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":2,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-01-03T08:37:46Z","registered":"2019-01-03T08:37:48Z","published":null,"updated":"2025-05-26T17:20:35Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100565","type":"dois","attributes":{"doi":"10.5524/100565","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Justin","familyName":"Jiang","name":"Jiang, Justin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Andrea, M","familyName":"Quattrini","name":"Quattrini, Andrea, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4247-3055"}],"affiliation":[]},{"nameType":"Personal","givenName":"Warren, R","familyName":"Francis","name":"Francis, Warren, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Joseph, F","familyName":"Ryan","name":"Ryan, Joseph, F","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5478-0522"}],"affiliation":[]},{"nameType":"Personal","givenName":"Estefanía","familyName":"Rodríguez","name":"Rodríguez, Estefanía","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Catherine, S","familyName":"McFadden","name":"McFadden, Catherine, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"A Hybrid de novo Assembly of the Sea Pansy (\u003ci\u003eRenilla muelleri\u003c/i\u003e) Genome\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"hybrid assembly","lang":"en-US"},{"subject":"gene prediction","lang":"en-US"},{"subject":"augustus","lang":"en-US"},{"subject":"pacbio","lang":"en-US"},{"subject":"masurca","lang":"en-US"},{"subject":"octocoral","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-02-28","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz026","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA491947","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://rmue.reefgenomics.org/","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["903.36 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Over 3,000 species of octocorals (Cnidaria, Anthozoa) inhabit an expansive range of environments, from shallow tropical seas to the deep-ocean floor. They are important foundation species that create coral forests, which provide unique niches and three-dimensional living space for other organisms. The octocoral genus \u003ci\u003eRenilla\u003c/i\u003e inhabits sandy, continental shelves in the subtropical and tropical Atlantic and eastern Pacific Oceans. \u003ci\u003eRenilla\u003c/i\u003e is especially interesting because it produces secondary metabolites for defense, exhibits bioluminescence, and produces a luciferase that is widely used in dual-reporter assays in molecular biology. Although several cnidarian genomes are currently available, the majority of these are hexacorals. Here, we present a de novo assembly of an azooxanthellate shallow-water octocoral, \u003ci\u003eR. muelleri\u003c/i\u003e. \u003cbr\u003eWe generated a hybrid de novo assembly using the Maryland Super-Read Celera Assembler v.3.2.6 (MaSuRCA). The final assembly included 4,825 scaffolds and a haploid genome size of 172 Mb. A BUSCO assessment found 88% of metazoan orthologs present in the genome. An Augustus ab initio gene prediction found 23,660 genes, of which 66% (15,635) had detectable similarity to annotated genes from the starlet sea anemone, \u003ci\u003eNematostella vectensis\u003c/i\u003e or to the Uniprot database. Although the \u003ci\u003eR. muelleri\u003c/i\u003egenome may be smaller (172 Mb minimum size) than other publicly available coral genomes (256-448 Mb), the \u003ci\u003eR. muelleri\u003c/i\u003e genome is similar to other coral genomes in terms of the number of complete metazoan BUSCOs and predicted gene models.\u003cbr\u003e The \u003ci\u003eR. mueller\u003c/i\u003ei hybrid genome provides a novel resource for researchers to investigate the evolution of genes and gene families within Octocorallia and more widely across Anthozoa. It will be a key resource for future comparative genomics with other corals and for understanding the genomic basis of coral diversity.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1457817"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1457581"},{"funderIdentifierType":"Crossref Funder ID","funderName":"University of Florida DSP Research Strategic Initiatives","awardNumber":"00114464"},{"funderIdentifierType":"Crossref Funder ID","funderName":"University of Florida Office of the Provost Programs"}],"url":"http://gigadb.org/dataset/100565","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-02-28T15:39:09Z","registered":"2019-02-28T15:39:10Z","published":null,"updated":"2025-05-26T17:20:34Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100552","type":"dois","attributes":{"doi":"10.5524/100552","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Henrik","familyName":"Krehenwinkel","name":"Krehenwinkel, Henrik","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5069-8601"}],"affiliation":[]},{"nameType":"Personal","givenName":"Aaron","familyName":"Pomerantz","name":"Pomerantz, Aaron","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6412-9001"}],"affiliation":[]},{"nameType":"Personal","givenName":"James, B","familyName":"Henderson","name":"Henderson, James, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Susan, R","familyName":"Kennedy","name":"Kennedy, Susan, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1616-3985"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jun, Ying","familyName":"Lim","name":"Lim, Jun, Ying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7493-2159"}],"affiliation":[]},{"nameType":"Personal","givenName":"Varun","familyName":"Swamy","name":"Swamy, Varun","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9203-212X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Juan, Diego","familyName":"Shoobridge","name":"Shoobridge, Juan, Diego","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Natalie","familyName":"Graham","name":"Graham, Natalie","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Nipam, H","familyName":"Patel ","name":"Patel , Nipam, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4328-654X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rosemary, G","familyName":"Gillespie","name":"Gillespie, Rosemary, G","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0086-7424"}],"affiliation":[]},{"nameType":"Personal","givenName":"Stefan","familyName":"Prost","name":"Prost, Stefan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6229-3596"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Nanopore sequencing of long ribosomal DNA amplicons enables portable and simple biodiversity assessments with high phylogenetic resolution across broad taxonomic scale\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Metabarcoding","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"minion","lang":"en-US"},{"subject":"metabarcoding","lang":"en-US"},{"subject":"biodiversity","lang":"en-US"},{"subject":"ribosomal","lang":"en-US"},{"subject":"eukaryotes","lang":"en-US"},{"subject":"long dna barcodes","lang":"en-US"},{"subject":"oxford nanopore technologies","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-03-01","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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shifts in global ecosystems. Current barcoding protocols often rely on short amplicon sequences, which yield accurate identification of biological entities in a community, but provide limited phylogenetic resolution across broad taxonomic scales. However, the phylogenetic structure of communities is an essential component of biodiversity. Consequently, a barcoding approach is required that unites robust taxonomic assignment power and high phylogenetic utility. A possible solution is offered by sequencing long ribosomal DNA (rDNA) amplicons on the MinION platform (Oxford Nanopore Technologies).\u003cbr\u003e Using a dataset of various animal and plant species, with a focus on arthropods, we assemble a pipeline for long rDNA barcode analysis and introduce a new software (MiniBar) to demultiplex dual indexed nanopore reads. We find excellent phylogenetic and taxonomic resolution offered by long rDNA sequences across broad taxonomic scales. We highlight the simplicity of our approach by field barcoding with a miniaturized, mobile laboratory in a remote rainforest. We also test the utility of long rDNA amplicons for analysis of community diversity through metabarcoding and find that they recover highly skewed diversity estimates.\u003cbr\u003eSequencing dual indexed, long rDNA amplicons on the MinION platform is a straightforward, cost effective, portable and universal approach for eukaryote DNA barcoding. Although bulk community analyses using long-amplicon approaches may introduce biases, the long rDNA amplicons approach signifies a powerful tool for enabling the accurate recovery of taxonomic and phylogenetic diversity across biological communities.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Liangbiao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0717-8536"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ying","familyName":"Lu","name":"Lu, Ying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wenhao","familyName":"Li","name":"Li, Wenhao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yandong","familyName":"Ren","name":"Ren, Yandong","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mengchao","familyName":"Yu","name":"Yu, Mengchao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Shouwen","familyName":"Jiang","name":"Jiang, Shouwen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yanxia","familyName":"Fu","name":"Fu, Yanxia","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jian","familyName":"Wang","name":"Wang, Jian","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sihua","familyName":"Peng","name":"Peng, Sihua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kevin, T","familyName":"Bilyk","name":"Bilyk, Kevin, T","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2262-2703"}],"affiliation":[]},{"nameType":"Personal","givenName":"Katherine, R","familyName":"Murphy","name":"Murphy, Katherine, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8898-8719"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xuan","familyName":"Zhuang","name":"Zhuang, Xuan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mathias","familyName":"Hune","name":"Hune, Mathias","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wanying","familyName":"Zhai","name":"Zhai, Wanying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wen","familyName":"Wang","name":"Wang, Wen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Qianghua","familyName":"Xu","name":"Xu, Qianghua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chi-Hing, Christina","familyName":"Cheng","name":"Cheng, Chi-Hing, Christina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Genomic bases for colonizing the freezing Southern Ocean revealed by the genomes of Antarctic toothfish and Patagonia robalo\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience 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The bottom-dwelling Eocene ancestor of Antarctic notothenioid fishes survived polar marine glaciation and underwent adaptive radiation forming \u0026gt;120 species that fill all water column niches today. Genome-wide changes enabling physiological adaptations and rapid expansion of the Antarctic Notothenioids remain poorly understood. To advance our understanding, we sequenced and compared two notothenioid genomes - the cold-adapted and neutrally buoyant Antarctic toothfish \u003ci\u003eDissostichus mawsoni\u003c/i\u003e, and the basal Patagonia robaloEleginops maclovinus representing the temperate ancestor. We detected \u0026gt;200 protein gene families that had expanded and thousands of genes that had evolved faster in the toothfish, with diverse cold-relevant functions including stress response, lipid metabolism, protein homeostasis and freeze resistance. Besides AFGP, an eggshell protein had functionally diversified to aid in cellular freezing resistance. Genomic and transcriptomic comparisons revealed proliferation of Selcys-tRNA genes and broad transcriptional upregulation across anti-oxidative selenoproteins, signifying their prominent role in mitigating oxidative stress in the oxygen-rich Southern Ocean. We found expansion of transposable elements, temporally correlated to Antarctic notothenioid diversification. In addition, the toothfish exhibited remarkable shifts in genetic programs towards enhanced fat cell differentiation and lipid storage, and promotion of chondrogenesis while inhibiting osteogenesis in bone development, collectively contributing to achieving neutral buoyancy and pelagicism. Our study revealed a comprehensive landscape of evolutionary changes essential for Antarctic notothenioid cold adaptation and ecological expansion. The two genomes are valuable resources for further uncovering mechanisms underlying the spectacular notothenioids radiation driven by the coldest environment.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"41761134050"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572611"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572598"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Shanghai Education Committee","awardNumber":"2017-01-07-00-10-E00060"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"ANT1142158"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Key Achievement Supporting Grant from Laboratory for Marine Biology \u0026 Biotechnology"}],"url":"http://gigadb.org/dataset/100545","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-01-18T09:39:34Z","registered":"2019-01-18T09:39:36Z","published":null,"updated":"2025-05-26T17:20:33Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100547","type":"dois","attributes":{"doi":"10.5524/100547","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Illyoung","familyName":"Choi","name":"Choi, Illyoung","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alise, J","familyName":"Ponsero","name":"Ponsero, Alise, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew","familyName":"Bomhoff","name":"Bomhoff, Matthew","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ken","familyName":"Youens-Clark","name":"Youens-Clark, Ken","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"John, H","familyName":"Hartman","name":"Hartman, John, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bonnie, L","familyName":"Hurwitz","name":"Hurwitz, Bonnie, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8699-957X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Libra: scalable k-mer based tool for massive all-vs-all metagenome comparisons.\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2018,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"Metagenomic","lang":"en-US"},{"subject":"metagenomics","lang":"en-US"},{"subject":"clustering","lang":"en-US"},{"subject":"distance metrics","lang":"en-US"},{"subject":"k-mer","lang":"en-US"},{"subject":"hadoop","lang":"en-US"}],"contributors":[],"dates":[{"date":"2018-12-17","dateType":"Available"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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Yet, inferences from metagenomic studies are often limited by dataset size and complexity, and are restricted by the availability and completeness of existing databases. De novo comparative metagenomics enables the comparison of metagenomes based on their total genetic content.\u003cbr\u003eWe developed a tool called Libra that performs all-vs-all comparison of metagenomes for precise clustering based on their k-mer content. Libra uses a scalable Hadoop framework for massive metagenome comparisons, Cosine Similarity for calculating the distance using sequence composition and abundance while normalizing for sequencing depth, and a web-based implementation in iMicrobe (http://imicrobe.us) that uses the CyVerse advanced cyberinfrastructure to promote broad use of the tool by the scientific community. \u003cbr\u003eA comparison of Libra to equivalent tools using both simulated and real metagenomic datasets, ranging from 80 million to 4.2 billion reads, reveals that methods commonly implemented to reduce compute time for large datasetssuch as data reduction, read count normalization, and presence/absence distance metricsgreatly diminish the resolution of large-scale comparative analyses. In contrast, Libra uses all of the reads to calculate k-mer abundance in a Hadoop architecture that can scale to any size dataset to enable global-scale analyses and link microbial signatures to biological processes.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1640775"}],"url":"http://gigadb.org/dataset/100547","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-12-17T16:06:35Z","registered":"2018-12-17T16:06:41Z","published":null,"updated":"2025-05-26T17:20:33Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100611","type":"dois","attributes":{"doi":"10.5524/100611","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Ken","familyName":"Youens-Clark","name":"Youens-Clark, Ken","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9961-144X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matt","familyName":"Bomhoff","name":"Bomhoff, Matt","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-8014-9184"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alise","familyName":"Ponsero","name":"Ponsero, Alise","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4125-7561"}],"affiliation":[]},{"nameType":"Personal","givenName":"Elisha, M","familyName":"Wood-Charlson","name":"Wood-Charlson, Elisha, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9557-7715"}],"affiliation":[]},{"nameType":"Personal","givenName":"Joshua","familyName":"Lynch","name":"Lynch, Joshua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6032-841X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Illyoung","familyName":"Choi","name":"Choi, Illyoung","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9705-6355"}],"affiliation":[]},{"nameType":"Personal","givenName":"John, H","familyName":"Hartman","name":"Hartman, John, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5557-0604"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bonnie, L","familyName":"Hurwitz","name":"Hurwitz, Bonnie, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8699-957X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"iMicrobe: Tools and data-driven discovery platform for the microbiome sciences\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Workflow","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"cyberinfrastructure","lang":"en-US"},{"subject":"cloud 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To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community.\u003cbr\u003eThe iMicrobe platform brings together analysis tools and microbiome data sets by leveraging National Science Foundation-supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly-scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP).\u003cbr\u003eiMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a webbased platform.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Gordon and Betty Moore Foundation","funderIdentifier":"https://doi.org/10.13039/100000936","awardNumber":"4491"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1639588"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Simons Foundation","funderIdentifier":"https://doi.org/10.13039/100000893"}],"url":"http://gigadb.org/dataset/100611","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":2,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-06-19T11:51:27Z","registered":"2019-06-19T11:51:29Z","published":null,"updated":"2025-05-26T17:20:28Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100578","type":"dois","attributes":{"doi":"10.5524/100578","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Matthew, A","familyName":"Conte","name":"Conte, Matthew, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2712-7960"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rajesh","familyName":"Joshi","name":"Joshi, Rajesh","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4363-0817"}],"affiliation":[]},{"nameType":"Personal","givenName":"Emily, C","familyName":"Moore","name":"Moore, Emily, C","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sri, Pratima","familyName":"Nandamuri","name":"Nandamuri, Sri, Pratima","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1445-7426"}],"affiliation":[]},{"nameType":"Personal","givenName":"William, J","familyName":" Gammerdinger","name":" Gammerdinger, William, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9638-1220"}],"affiliation":[]},{"nameType":"Personal","givenName":"Reade, B","familyName":"Roberts","name":"Roberts, Reade, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2551-3761"}],"affiliation":[]},{"nameType":"Personal","givenName":"Karen, L","familyName":"Carleton","name":"Carleton, Karen, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6306-5643"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sigbjørn","familyName":"Lien","name":"Lien, Sigbjørn","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Thomas, D","familyName":"Kocher","name":"Kocher, Thomas, D","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7547-0133"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Chromosome-scale assemblies reveal the structural evolution of African cichlid genomes\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"karyotype","lang":"en-US"},{"subject":"inversion","lang":"en-US"},{"subject":"recombination","lang":"en-US"},{"subject":"transposable elements","lang":"en-US"},{"subject":"genetic maps","lang":"en-US"},{"subject":"genome assembly","lang":"en-US"},{"subject":"african cichlids","lang":"en-US"},{"subject":"comparative genomics","lang":"en-US"},{"subject":"genome 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Here we compare multiple, high-quality, chromosome scale genome assemblies to understand the genetic mechanisms underlying cichlid diversification and study how genome structure evolves in rapidly radiating lineages.\u003cbr\u003e We re-anchored our recent assembly of the Nile tilapia (\u003ci\u003eOreochromis niloticus\u003c/i\u003e) genome using a new high-density genetic map. We developed a new de novo genome assembly of the Lake Malawi cichlid, \u003ci\u003eMetriaclima zebra\u003c/i\u003e, using high-coverage PacBio sequencing, and anchored contigs to linkage groups (LGs) using four different genetic maps. These new anchored assemblies allow the first chromosome-scale comparisons of African cichlid genomes. Large intra-chromosomal structural differences (~2-28Mbp) among species are common, while inter-chromosomal differences are rare (\u0026lt; 10Mbp total). Placement of the centromeres within chromosome-scale assemblies identifies large structural differences that explain many of the karyotype differences among species. Structural differences are also associated with unique patterns of recombination on sex chromosomes. Structural differences on LG9, LG11 and LG20 are associated with reductions in recombination, indicative of inversions between the rock- and sanddwelling clades of Lake Malawi cichlids. \u003ci\u003eM. zebra\u003c/i\u003e has a larger number of recent transposable element (TE) insertions compared to \u003ci\u003eO. niloticus\u003c/i\u003e, suggesting that several TE families have a higher rate of insertion in the haplochromine cichlid lineage.\u003cbr\u003eThis study identifies novel structural variation among East African cichlid genomes and provides a new set of genomic resources to support research on the mechanisms driving cichlid adaptation and speciation.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"U.S. Department of Agriculture","funderIdentifier":"https://doi.org/10.13039/100000199","awardNumber":"MD.W-2014-05906"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Wei","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7846-0491"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xuepeng","familyName":"Sun","name":"Sun, Xuepeng","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3471-8275"}],"affiliation":[]},{"nameType":"Personal","givenName":"Junyang","familyName":"Yue","name":"Yue, Junyang","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xiaofeng","familyName":"Tang","name":"Tang, Xiaofeng","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chen","familyName":"Jiao","name":"Jiao, Chen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ying","familyName":"Yang","name":"Yang, Ying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xiangli","familyName":"Niu","name":"Niu, Xiangli","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Min","familyName":"Miao","name":"Miao, Min","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Danfeng","familyName":"Zhang","name":"Zhang, Danfeng","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Shengxiong","familyName":"Huang","name":"Huang, Shengxiong","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wei","familyName":"Shi","name":"Shi, Wei","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mingzhang","familyName":"Li","name":"Li, Mingzhang","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Congbing","familyName":"Fang","name":"Fang, Congbing","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Zhangjun","familyName":"Fei","name":"Fei, Zhangjun","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9684-1450"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yongsheng","familyName":"Liu","name":"Liu, Yongsheng","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Chromosome-scale genome assembly of kiwifruit Actinidia eriantha with single-molecule sequencing and chromatin interaction mapping\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"kiwifruit","lang":"en-US"},{"subject":"actinidia eriantha","lang":"en-US"},{"subject":"genome assembly","lang":"en-US"},{"subject":"single molecular sequencing","lang":"en-US"},{"subject":"hi-c","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-02-19","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz027","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA480681","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"http://bdg.hfut.edu.cn/kir/","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Workflow","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["279.91 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A handful of kiwifruit species have been domesticated, among which the A. eriantha is increasingly favored in breeding due to its superior commercial traits. Recently, elite cultivars from A. eriantha have been successfully selected and further studies on their biology and breeding potential require genomic information which is currently unavailable. Here, we provide a high quality A. eriantha genome as well as its gene annotation. Availability of these data will facilitate the breeding program in the future.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Government of Sichuan Province","awardNumber":"2016NZ0105"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Natural Science Foundation of China","funderIdentifier":"https://doi.org/10.13039/501100001809","awardNumber":"31471157"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IOS-1339287"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Natural Science Foundation of China","funderIdentifier":"https://doi.org/10.13039/501100001809","awardNumber":"31700266"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Foundation for Germplasm Repository of Special Horticultural Crops in Central Mountain Areas of China","awardNumber":"NJF2017-69"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Fund for Distinguished Young Scholars","awardNumber":"30825030"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Government of Sichuan Province","awardNumber":"2013NZ0014"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Government of Anhui Province","awardNumber":"2012AKKG0739"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IOS-1539831"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Government of Anhui Province","awardNumber":"1808085MC57"}],"url":"http://gigadb.org/dataset/100568","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-02-19T07:34:20Z","registered":"2019-02-19T07:34:21Z","published":null,"updated":"2025-05-26T17:20:27Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100627","type":"dois","attributes":{"doi":"10.5524/100627","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Eric, J","familyName":"Carpenter","name":"Carpenter, Eric, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Naim","familyName":"Matasci","name":"Matasci, 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Rocha","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chris","familyName":"Bowler","name":"Bowler, Chris","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Richard, G","familyName":"Dorrell","name":"Dorrell, Richard, G","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew, A","familyName":"Gitzendanner","name":"Gitzendanner, Matthew, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ling","familyName":"Li","name":"Li, Ling","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wensi","familyName":"Du","name":"Du, 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H","familyName":"Leebens-Mack","name":"Leebens-Mack, James, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gane, Ka-Shu","familyName":"Wong","name":"Wong, Gane, Ka-Shu","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6108-5560"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Data supporting the 1000 plant (1KP) transcriptomes initiative"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Transcriptomic","lang":"en-US"},{"subject":"rna","lang":"en-US"},{"subject":"plants","lang":"en-US"},{"subject":"assemblies","lang":"en-US"},{"subject":"genes","lang":"en-US"},{"subject":"contamination","lang":"en-US"},{"subject":"completeness","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-10-23","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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All of the analyses done for the 1KP capstone, and previous studies on subsets of these data, are based on a series of de novo transcriptome assemblies and related outputs that will be described in the accompanying GigaScience publication. We also describe assessments of the data quality and an analysis to remove cross-contamination between the samples. These data will be useful to researchers with interests in specific gene families, either across the green plant tree of life or in more focused lineages.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Alberta Ministry of Advanced Education","awardNumber":"RES0010334"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The National Key Research and Development Program of China"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ministry of Science and Technology of the People's Republic of China","awardNumber":"2015BAD04B01/2015BAD04B03"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ministry of Science and Technology of the People's Republic of China","awardNumber":"2011DQ782025"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Guangdong Province","awardNumber":"2011A091000047"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Shenzhen Municipal Government of 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Myeloma Progression Integrating Gene Expression and Clinical Features\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2019,"subjects":[{"subject":"Transcriptomic","lang":"en-US"},{"subject":"multiple myeloma","lang":"en-US"},{"subject":"prognostic model","lang":"en-US"},{"subject":"survival analysis","lang":"en-US"},{"subject":"guanrank","lang":"en-US"},{"subject":"gene signature","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-12-05","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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With the increase in treatment options, risk-adapted therapy is becoming more and more important. Survival analysis is commonly applied to study progression or other events of interest and stratify the risk of patients. In this study, we present the current state-of-the-art model for MM prognosis and the molecular biomarker set for stratification: the winning algorithm in the 2017 Multiple Myeloma DREAM Challenge, Sub-Challenge 3. Specifically, we built a non-parametric complete hazard ranking model to map the right-censored data into a linear space, where commonplace machine learning techniques, such as Gaussian process regression and random forests, can play their roles. Our model integrated both the gene expression profile and clinical features to predict the progression of MM. Compared with conventional models, such as Cox model and Random Survival Forests, our model achieved higher accuracy in 3 within-cohort predictions. In addition, it showed robust predictive power in cross-cohort validations. Key molecular signatures related to MM progression were identified from our model, which may function as the core determinants of MM progression and provide important guidance value for future research and clinical practice. Functional enrichment analysis and mammalian gene-gene interaction network revealed crucial biological processes and pathways involved in MM progression. We present the current state-of-the-art prognostic model for Multiple Myeloma integrating gene expression and clinical features validated in independent test set.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"NSF-US14-PAF07599"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"5-P30-DK-081943-10"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Michigan Institute for Data Science (MIDAS)"}],"url":"http://gigadb.org/dataset/100684","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-06-23T13:05:42Z","registered":"2021-06-23T13:05:44Z","published":null,"updated":"2025-05-26T17:20:12Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100686","type":"dois","attributes":{"doi":"10.5524/100686","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Jaqueline, J.","familyName":"Brito","name":"Brito, Jaqueline, J.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Thiago","familyName":"Mosqueiro","name":"Mosqueiro, 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High-performance computational facilities are capable of processing considerable volumes of data, yet often lack an easy-to-use interface to guide the user in supervising and adjusting bioinformatics analysis via a tablet or smartphone. Telescope is a novel tool that interfaces with high-performance computational clusters to deliver an intuitive user interface for controlling and monitoring bioinformatics analyses in real-time. Telescope provides a user-friendly method for integrating computational analyses with experimental biomedical research.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1564899"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"CCF-1619110"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Health","awardNumber":"1R01EB025022-01"}],"url":"http://gigadb.org/dataset/100686","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-12-19T09:53:52Z","registered":"2019-12-19T09:53:53Z","published":null,"updated":"2025-05-26T17:20:10Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100726","type":"dois","attributes":{"doi":"10.5524/100726","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Nathan, J","familyName":"Kenny","name":"Kenny, Nathan, 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Arina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1336-2505"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sarah","familyName":"Pelan","name":"Pelan, Sarah","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8729-685X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yan","familyName":"Ryan","name":"Ryan, Yan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4708-5350"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ying","familyName":"Sims","name":"Sims, Ying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jason","familyName":"Skelton","name":"Skelton, 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Anil","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7310-4191"}],"affiliation":[]},{"nameType":"Personal","givenName":"Erez, Lieberman","familyName":"Aiden","name":"Aiden, Erez, Lieberman","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0634-6486"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kerstin","familyName":"Howe","name":"Howe, Kerstin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2237-513X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Suzanne, T","familyName":"Williams","name":"Williams, Suzanne, T","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2995-5823"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"The Gene-Rich Genome of the Scallop Pecten maximus\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2020,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"scallop","lang":"en-US"},{"subject":"bivalve","lang":"en-US"},{"subject":"mollusc","lang":"en-US"},{"subject":"genome","lang":"en-US"},{"subject":"domoic","lang":"en-US"},{"subject":"neurotoxin","lang":"en-US"}],"contributors":[],"dates":[{"date":"2020-03-19","dateType":"Available"},{"date":"2020","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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It forms the basis of a valuable commercial fishery and its ubiquity means that it plays a key role in coastal ecosystems and food webs. Like other filter feeding bivalves it can accumulate potent phytotoxins, to which it has evolved some immunity. The molecular origins of this immunity are of interest to evolutionary biologists, pharmaceutical companies and fisheries management. \u003cbr\u003eHere we report the genome sequencing of this species, conducted as part of the Wellcome Sanger 25 Genomes Project. This genome was assembled from PacBio reads and scaffolded with 10x Chromium and Hi-C data, and its 3,983 scaffolds have an N50 of 44.8 Mb (longest scaffold 60.1 Mb), with 92% of the assembly sequence contained in 19 scaffolds, corresponding to the 19 chromosomes found in this species. The total assembly spans 918.3 Mb, and is the best-scaffolded marine bivalve genome published to date, exhibiting 95.5% recovery of the metazoan BUSCO set. Gene annotation resulted in 67,741 gene models. Analysis of gene content revealed large numbers of gene duplicates, as previously seen in bivalves, with little gene loss, in comparison with the sequenced genomes of other marine bivalve species. \u003cbr\u003eThe genome assembly of \u003ci\u003ePecten maximus\u003c/i\u003e and its annotated gene set provide a high-quality platform for a wide range of investigations, including studies on such disparate topics as shell biomineralization, pigmentation, vision and resistance to algal toxins. As a result of our findings we highlight the sodium channel gene Nav1, known as a gene conferring resistance to saxitoxin and tetrodotoxin, as a candidate for further studies investigating immunity to domoic acid.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural History Museum(NHM)","awardNumber":"SDR17012"},{"funderIdentifierType":"Crossref Funder ID","funderName":"H2020 Marie Skłodowska-Curie Actions","funderIdentifier":"https://doi.org/10.13039/100010665","awardNumber":"750937"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Wellcome Trust","funderIdentifier":"https://doi.org/10.13039/100004440","awardNumber":"WT207492"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"PHY1427654"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Welch Foundation","funderIdentifier":"https://doi.org/10.13039/100000928","awardNumber":"Q-1866"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"U01HL130010"},{"funderIdentifierType":"Crossref Funder ID","funderName":"DNA Genotek (CA)","awardNumber":"UM1HG009375"},{"funderIdentifierType":"Crossref Funder ID","funderName":"U.S. Department of Agriculture","funderIdentifier":"https://doi.org/10.13039/100000199","awardNumber":"2017-05741"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Marie Curie Alumni Association","awardNumber":"N/A"}],"url":"http://gigadb.org/dataset/100726","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2020-03-19T13:08:36Z","registered":"2020-03-19T13:08:38Z","published":null,"updated":"2025-05-26T17:20:05Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100816","type":"dois","attributes":{"doi":"10.5524/100816","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Ariel","familyName":"Rokem","name":"Rokem, Ariel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0679-1985"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kendrick","familyName":"Kay","name":"Kay, Kendrick","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6604-9155"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Fractional ridge regression: a fast, interpretable reparameterization of ridge regression\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2020,"subjects":[{"subject":"Imaging","lang":"en-US"},{"subject":"Neuroscience","lang":"en-US"},{"subject":"generalized linear model","lang":"en-US"},{"subject":"hyperparameters","lang":"en-US"},{"subject":"brain imaging","lang":"en-US"}],"contributors":[],"dates":[{"date":"2020-10-28","dateType":"Available"},{"date":"2020","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giaa133","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://zenodo.org/record/3923102#.X4BjAJP0lcB","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/nrdg/fracridge","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/kendrickkay/knkutils/","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Ridge regression is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using ridge regression is the need to set a hyperparameter () that controls the amount of regularization. Cross-validation is typically used to select the best from a set of candidates. However, efficient and appropriate selection of can be challenging. This becomes prohibitive when large amounts of data are analyzed. Because the selected depends on the scale of the data and correlations across predictors, it is also not straightforwardly interpretable.\u003cbr\u003eThe present work addresses these challenges through a novel approach to ridge regression. We propose to reparameterize ridge regression in terms of the ratio between the L2-norms of the regularized and unregularized coefficients. We provide an algorithm that efficiently implements this approach, called fractional ridge regression, as well as open-source software implementations in Python and MATLAB (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems. In brain imaging data, we demonstrate that this approach delivers results that are straightforward to interpret and compare across models and datasets.\u003cbr\u003eFractional ridge regression has several benefits: the solutions obtained for different are guaranteed to vary, guarding against wasted calculations, and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. These properties make fractional ridge regression particularly suitable for analysis of large complex datasets.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Mental Health","funderIdentifier":"https://doi.org/10.13039/100000025","awardNumber":"1RF1MH121868-01"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Gordon and Betty Moore Foundation (US)","awardNumber":"2013-10-29"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Alfred P. Sloan Foundation","funderIdentifier":"https://doi.org/10.13039/100000879","awardNumber":"3835"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Biomedical Imaging and Bioengineering","funderIdentifier":"https://doi.org/10.13039/100000070","awardNumber":"5R01EB027585-02"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1934292"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of Biomedical Imaging and Bioengineering","funderIdentifier":"https://doi.org/10.13039/100000070","awardNumber":"P41 EB015894"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"S10 RR026783"},{"funderIdentifierType":"Crossref Funder ID","funderName":"W. M. Keck Foundation (US)"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IIS-1822683"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IIS-1822929"}],"url":"http://gigadb.org/dataset/100816","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2020-10-28T10:47:20Z","registered":"2020-10-28T10:47:22Z","published":null,"updated":"2025-05-26T17:19:56Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100796","type":"dois","attributes":{"doi":"10.5524/100796","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Alexandra, J","familyName":"Lee","name":"Lee, Alexandra, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"YoSon","familyName":"Park","name":"Park, YoSon","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0465-4744"}],"affiliation":[]},{"nameType":"Personal","givenName":"Georgia","familyName":"Doing","name":"Doing, Georgia","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0835-6955"}],"affiliation":[]},{"nameType":"Personal","givenName":"Deborah, A","familyName":"Hogan","name":"Hogan, Deborah, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6366-2971"}],"affiliation":[]},{"nameType":"Personal","givenName":"Casey, S","familyName":"Greene","name":"Greene, Casey, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8713-9213"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Correcting for experiment-specific variability in expression compendia can remove underlying signals\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2020,"subjects":[{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Software","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"gene expression","lang":"en-US"},{"subject":"batch effect","lang":"en-US"},{"subject":"neural network","lang":"en-US"},{"subject":"variational autoencoder","lang":"en-US"}],"contributors":[],"dates":[{"date":"2020-09-25","dateType":"Available"},{"date":"2020","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giaa117","relatedIdentifierType":"DOI"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/greenelab/simulate-expression-compendia","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"In the last two decades, scientists working in different labs have assayed gene expression from millions of samples. These experiments can be combined into compendia and analyzed collectively to extract novel biological patterns. Technical variability, sometimes referred to as batch effects, may result from combining samples collected and processed at different times and in different settings. Such variability may distort our ability to interpret and extract true underlying biological patterns. As more integrative analysis methods are developed and available data collections are increased in size, it is crucial to determine how technical variability affect our ability to detect desired patterns when many experiments are combined.\u003cbr\u003eWe sought to determine the extent to which an underlying signal was masked by technical variability by simulating compendia comprised of data aggregated across multiple experiments.\u003cbr\u003eWe developed a generative multi-layer neural network to simulate compendia of gene expression experiments from large-scale microbial and human datasets. We compared simulated compendia before and after introducing varying numbers of sources of undesired variability.\u003cbr\u003eWe found that the signal from a baseline compendium was obscured when the number of added sources of variability was small. Perhaps as expected, applying statistical correction methods rescued the underlying signal in these cases. However, as the number of sources of variability increased we observed that detecting the original signal became increasingly easier even without correction. In fact, applying statistical correction methods reduced our power to detect the underlying signal.\u003cbr\u003eWhen combining a modest number of experiments, it is best to correct for experiment-specific noise. However, when many experiments are combined, statistical correction reduces our ability to extract underlying patterns.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Cystic Fibrosis Foundation","funderIdentifier":"https://doi.org/10.13039/100000897","awardNumber":"HOGAN19G0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Cystic Fibrosis Foundation","funderIdentifier":"https://doi.org/10.13039/100000897","awardNumber":"STANTO19R0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1458359"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of General Medical Sciences","funderIdentifier":"https://doi.org/10.13039/100000057","awardNumber":"5T32GM008704"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Gordon and Betty Moore Foundation","funderIdentifier":"https://doi.org/10.13039/100000936","awardNumber":"GBMF 4552"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Human Genome Research Institute","funderIdentifier":"https://doi.org/10.13039/100000051","awardNumber":"R01 HG010067"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Cancer Institute","funderIdentifier":"https://doi.org/10.13039/100000054","awardNumber":"R01 CA237170"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Cancer Institute","funderIdentifier":"https://doi.org/10.13039/100000054","awardNumber":"R01CA200854"}],"url":"http://gigadb.org/dataset/100796","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2020-09-25T13:02:49Z","registered":"2020-09-25T13:02:51Z","published":null,"updated":"2025-05-26T17:19:55Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100856","type":"dois","attributes":{"doi":"10.5524/100856","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Emily, A","familyName":"Ellis","name":"Ellis, Emily, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3343-0923"}],"affiliation":[]},{"nameType":"Personal","givenName":"Caroline, G","familyName":"Storer","name":"Storer, Caroline, G","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Akito, Y","familyName":"Kawahara","name":"Kawahara, Akito, Y","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3724-4610"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"\u003ci\u003eDe-novo\u003c/i\u003e genome assemblies of butterflies\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"life sciences","lang":"en-US"},{"subject":"open data","lang":"en-US"},{"subject":"papilionoidea","lang":"en-US"},{"subject":"accessibility","lang":"en-US"},{"subject":"genomics","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-03-08","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giab041","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA606954","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The current genomic age has led to the availability of thousands of genomes and enabled new advancements in biology. However, as the number of genomes increases, considerable attention should be given to their quality. Here we examine these trends in a taxonomically diverse and well-known group, butterflies, and provide draft, \u003ci\u003ede-novo\u003c/i\u003e assemblies for all available butterfly genomes. Due to massive genome sequencing investment and taxonomic curation, this is an excellent group to explore genome quality. We provide \u003ci\u003ede-novo\u003c/i\u003e assemblies for all 822 available butterfly genomes and interpret their quality in terms of completeness and continuity. Further, we discuss reuse cases and provide general guidelines in these cases. These assemblies will serve as a key resource for papilionoid genomics, especially for researchers without computational resources. We identify the 50 highest quality genomes across butterflies, and conclude that the ringlet, \u003ci\u003eAphantopus hyperantus\u003c/i\u003e has the highest quality papilionoid genome. Our post-processing of these draft genome assemblies identified 118 butterfly genomes that should not be reused due to contamination or extremely low quality. However, many draft genomes are of high utility, especially because permissibility of low-quality genomes is dependent on the objective of the study. Quality metrics and assemblies are typically presented with annotated genome accessions, but rarely with \u003ci\u003ede-novo\u003c/i\u003e genomes. We recommend that studies presenting genome sequences provide the assembly and some metrics of quality, as quality will significantly impact downstream results. Transparency in quality metrics are needed to improve the field of genome science and encourage data reuse.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1541500"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1557007"}],"url":"http://gigadb.org/dataset/100856","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-03-08T09:39:29Z","registered":"2021-03-08T09:39:30Z","published":null,"updated":"2025-05-26T17:19:46Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100913","type":"dois","attributes":{"doi":"10.5524/100913","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Aundrea, K","familyName":"Westfall","name":"Westfall, Aundrea, K","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4849-4831"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rory, S","familyName":"Telemeco","name":"Telemeco, Rory, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0767-8565"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mariana, B","familyName":"Grizante","name":"Grizante, Mariana, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5209-8589"}],"affiliation":[]},{"nameType":"Personal","givenName":"Damien, S","familyName":"Waits","name":"Waits, Damien, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0973-8629"}],"affiliation":[]},{"nameType":"Personal","givenName":"Amanda, D","familyName":"Clark","name":"Clark, Amanda, D","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1186-3114"}],"affiliation":[]},{"nameType":"Personal","givenName":"Dasia, Y","familyName":"Simpson","name":"Simpson, Dasia, Y","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2304-093X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Randy, L","familyName":"Klabacka","name":"Klabacka, Randy, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3924-0143"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alexis, P","familyName":"Sullivan","name":"Sullivan, Alexis, P","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9296-8112"}],"affiliation":[]},{"nameType":"Personal","givenName":"George, H","familyName":"Perry","name":"Perry, George, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4527-3806"}],"affiliation":[]},{"nameType":"Personal","givenName":"Michael, W","familyName":"Sears","name":"Sears, Michael, W","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Christian, L","familyName":"Cox","name":"Cox, Christian, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9424-8482"}],"affiliation":[]},{"nameType":"Personal","givenName":"Robert, M","familyName":"Cox","name":"Cox, Robert, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8325-111X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew, E","familyName":"Gifford","name":"Gifford, Matthew, E","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1263-0010"}],"affiliation":[]},{"nameType":"Personal","givenName":"Henry, B","familyName":"John-Alder","name":"John-Alder, Henry, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5036-592X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tracy","familyName":"Langkilde","name":"Langkilde, Tracy","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7014-2432"}],"affiliation":[]},{"nameType":"Personal","givenName":"Michael, J","familyName":"Angilletta Jr","name":"Angilletta Jr, Michael, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Adam, D","familyName":"Leaché","name":"Leaché, Adam, D","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8929-6300"}],"affiliation":[]},{"nameType":"Personal","givenName":"Marc","familyName":"Tollis","name":"Tollis, Marc","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1917-2473"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kenro","familyName":"Kusumi","name":"Kusumi, Kenro","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1458-4540"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tonia, S","familyName":"Schwartz","name":"Schwartz, Tonia, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7712-2810"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"A chromosome-level genome assembly for the Eastern fence lizard (Sceloporus undulatus), a reptile model for physiological and evolutionary ecology\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"genome","lang":"en-US"},{"subject":"transcriptome","lang":"en-US"},{"subject":"squamate","lang":"en-US"},{"subject":"reptile","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-08-31","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giab066","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA371829","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA612440","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"High-quality genomic resources facilitate investigations into behavioral ecology, morphological and physiological adaptations, and the evolution of genomic architecture. Lizards in the genus \u003ci\u003eSceloporus\u003c/i\u003e have a long history as important ecological, evolutionary, and physiological models, making them a valuable target for the development of genomic resources.\u003cbr\u003e We present a high-quality chromosome-level reference genome assembly, SceUnd1.0, (utilizing 10X Genomics Chromium, HiC, and PacBio data) and tissue/developmental stage transcriptomes for the Eastern Fence Lizard, \u003ci\u003eSceloporus undulatus\u003c/i\u003e . We performed synteny analysis with other snake and lizard assemblies to identify broad patterns of chromosome evolution including the fusion of micro- and macrochromosomes. We also used this new assembly to provide improved reference-based genome assemblies for 34 additional \u003ci\u003eSceloporus\u003c/i\u003e species. Finally, we used RNAseq and whole-genome resequencing data to compare three assemblies, each representing an increased level of cost and effort: Supernova Assembly with data from 10X Genomics Chromium; HiRise Assembly that added data from HiC; and PBJelly Assembly that added data from PacBio sequencing. We found that the Supernova Assembly contained the full genome and was a suitable reference for RNAseq and SNP calling, but the chromosome-level scaffolds provided by the addition of HiC data allowed synteny and whole genome association mapping analyses. The subsequent addition of PacBio data doubled the contig N50 but provided negligible gains in scaffold length.\u003cbr\u003eThese new genomic resources provide valuable tools for advanced molecular analysis of an organism that has become a model in physiology and evolutionary ecology.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"University of Virginia","funderIdentifier":"https://doi.org/10.13039/100008457"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DGE 1414475"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DGE 1255832"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"BCS-1554834"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1855845"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1456655"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Clemson University","funderIdentifier":"https://doi.org/10.13039/100006498"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Georgia Southern Univsersity"},{"funderIdentifierType":"Crossref Funder ID","funderName":"School of Life Sciences at Arizona State University"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Hatch Multistate W3045","awardNumber":"NJ17240"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Auburn University","funderIdentifier":"https://doi.org/10.13039/100007579"}],"url":"http://gigadb.org/dataset/100913","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-08-31T13:13:15Z","registered":"2021-08-31T13:13:16Z","published":null,"updated":"2025-05-26T17:16:12Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100941","type":"dois","attributes":{"doi":"10.5524/100941","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Jeffrey, N","familyName":"Law","name":"Law, Jeffrey, N","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2828-1273"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kyle","familyName":"Akers","name":"Akers, Kyle","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5093-4619"}],"affiliation":[]},{"nameType":"Personal","givenName":"Nure","familyName":"Tasnina","name":"Tasnina, Nure","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Catherine, M","familyName":"Della-Santina","name":"Della-Santina, Catherine, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6693-1022"}],"affiliation":[]},{"nameType":"Personal","givenName":"Shay","familyName":"Deutsch","name":"Deutsch, Shay","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7623-6376"}],"affiliation":[]},{"nameType":"Personal","givenName":"Meghana","familyName":"Kshirsagar","name":"Kshirsagar, Meghana","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4673-614X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Judith","familyName":"Klein-Seetharaman","name":"Klein-Seetharaman, Judith","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4892-6828"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mark","familyName":"Crovella","name":"Crovella, Mark","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5005-7019"}],"affiliation":[]},{"nameType":"Personal","givenName":"Padmavathy","familyName":"Rajagopalan","name":"Rajagopalan, Padmavathy","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9997-4953"}],"affiliation":[]},{"nameType":"Personal","givenName":"Simon","familyName":"Kasif","name":"Kasif, Simon","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3297-9914"}],"affiliation":[]},{"nameType":"Personal","givenName":"T, M","familyName":"Murali","name":"Murali, T, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3688-4672"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Interpretable Network Propagation with Application to Expanding the Repertoire of Human Proteins that Interact with SARS-CoV-2\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"network propagation","lang":"en-US"},{"subject":"interpretable machine learning","lang":"en-US"},{"subject":"provenance tracing","lang":"en-US"},{"subject":"sars-cov-2","lang":"en-US"},{"subject":"covid-19","lang":"en-US"},{"subject":"virus-host protein interaction networks","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-11-02","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giab082","relatedIdentifierType":"DOI"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/Murali-group/SARS-CoV-2-network-analysis","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["50 MB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Network propagation has been widely used for nearly 20 years to predict gene functions and phenotypes. Despite the popularity of this approach, little attention has been paid to the question of provenance tracing in this context, e.g., determining how much any experimental observation in the input contributes to the score of every prediction. \u003cbr\u003eWe design a network propagation framework with two novel components and apply it to predict human proteins that directly or indirectly interact with SARS-CoV-2 proteins. First, we trace the provenance of each prediction to its experimentally validated sources, which in our case are human proteins experimentally determined to interact with viral proteins. Second, we design a technique that helps to reduce the manual adjustment of parameters by users. We find that for every top-ranking prediction, the highest contribution to its score arises from a direct neighbor in a human protein-protein interaction network. We further analyze these results to develop functional insights on SARS-CoV-2 that expand on known biology such as the connection between endoplasmic reticulum stress, HSPA5, and anti-clotting agents. \u003cbr\u003eWe examine how our provenance tracing method can be generalized to a broad class of network-based algorithms. We provide a useful resource for the SARS-CoV-2 community that implicates many previously undocumented proteins with putative functional relationships to viral infection. This resource includes potential drugs that can be opportunistically repositioned to target these proteins. We also discuss how our overall framework can be extended to other, newly-emerging viruses.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1759858"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"MCB-1817736"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"CCF-2029543"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"CNS-1618207"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Hariri Institute"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Boston University","funderIdentifier":"https://doi.org/10.13039/100007161"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"CBET-1510920"},{"funderIdentifierType":"Crossref Funder ID","funderName":"USDA-NIFA","awardNumber":"2018-07578"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Virginia Tech"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Virginia Tech"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Virginia Tech"}],"url":"http://gigadb.org/dataset/100941","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-11-02T10:50:47Z","registered":"2021-11-02T10:50:49Z","published":null,"updated":"2025-05-26T17:16:04Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100886","type":"dois","attributes":{"doi":"10.5524/100886","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Drew, J","familyName":"Duckett","name":"Duckett, Drew, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2410-3069"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jack","familyName":"Sullivan","name":"Sullivan, Jack","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0216-6867"}],"affiliation":[]},{"nameType":"Personal","givenName":"Stacy","familyName":"Pirro","name":"Pirro, Stacy","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5642-4203"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bryan, C","familyName":"Carstens","name":"Carstens, Bryan, C","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1552-227X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Genomic data for the North American water vole (Microtus richardsoni)"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"genome assembly","lang":"en-US"},{"subject":"genome annotation","lang":"en-US"},{"subject":"mitochondrial genome","lang":"en-US"},{"subject":"10x chromium","lang":"en-US"},{"subject":"illumina sequencing","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-04-14","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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Providing such resources would benefit future studies of immunology, phylogeography, cryptic diversity, and more. We sequenced and assembled nuclear genomes from two subspecies of water vole (\u003ci\u003eMicrotus richardsoni\u003c/i\u003e) and from the montane vole (\u003ci\u003eMicrotus montanus\u003c/i\u003e). \u003cbr\u003eThe North American water vole (\u003ci\u003eM. richardsoni\u003c/i\u003e) is adapted to a semi-aquatic lifestyle, relying on alpine and sub-alpine streams for creating burrows and escaping predators. The present study provides two nuclear and one mitochondrial genome assembly for \u003ci\u003eM. richardsoni\u003c/i\u003e. The nuclear genomes were sequenced with Illumina and 10X Chromium plus Illumina sequencing. Sequencing of \u003ci\u003eM. r. arvicoloides\u003c/i\u003e produced over 800 million reads and 47x coverage. The final genome assembly consisted of ~32,000 scaffolds with an N50 of 2.3 Mb, 1.3% missing data (N's), and a BUSCO score of 85.8%. Sequencing of \u003ci\u003eM. r. macropus\u003c/i\u003e produced over 600 million reads and 35x coverage. The final genome assembly consisted of ~1,600,000 scaffolds with an N50 of 16Kb, 0.06% missing data, and a BUSCO score of 54.5%. In addition to the nuclear assemblies, a mitochondrial genome assembly was also performed for \u003ci\u003eM. r. arvicoloides\u003c/i\u003e.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DEB-1457519"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ohio State University","awardNumber":"NA"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1945347"}],"url":"http://gigadb.org/dataset/100886","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-04-14T15:12:47Z","registered":"2021-04-14T15:12:49Z","published":null,"updated":"2025-05-26T17:15:42Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100908","type":"dois","attributes":{"doi":"10.5524/100908","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Michael","familyName":"Linderman","name":"Linderman, Michael","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9643-7148"}],"affiliation":[]},{"nameType":"Personal","givenName":"Crystal","familyName":"Paudyal","name":"Paudyal, Crystal","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5718-4515"}],"affiliation":[]},{"nameType":"Personal","givenName":"Musab","familyName":"Shakeel","name":"Shakeel, Musab","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1706-4652"}],"affiliation":[]},{"nameType":"Personal","givenName":"William","familyName":"Kelley","name":"Kelley, William","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ali","familyName":"Bashir","name":"Bashir, Ali","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5240-9604"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bruce, D.","familyName":"Gelb","name":"Gelb, Bruce, D.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8527-5027"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"NPSV: A simulation-driven approach to genotyping structural variants in whole genome sequencing data\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"structural variants","lang":"en-US"},{"subject":"next generation sequencing","lang":"en-US"},{"subject":"whole genome sequencing","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-06-01","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giab046","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://scicrunch.org/resolver/RRID:SCR_020984","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/mlinderm/npsv","relatedIdentifierType":"URL"},{"relationType":"Cites","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Structural variants (SV) play a causal role in numerous diseases but are difficult to detect and accurately genotype (determine zygosity) in whole genome next-generation sequencing (NGS) data. SV genotypers that assume the aligned sequencing data uniformly reflects the underlying SV or use existing SV call sets as training data can only partially account for variant and sample-specific biases. \u003cbr\u003eWe introduce NPSV, a machine learning-based approach for genotyping previously discovered SVs that employs NGS simulation to model the combined effects of the genomic region, sequencer and alignment pipeline on the observed SV evidence. We evaluate NPSV alongside existing SV genotypers on multiple benchmark call sets. We show that NPSV consistently achieves or exceeds state-of-the-art genotyping accuracy across SV call sets, samples and variant types. NPSV can specifically identify putative \u003ci\u003ede novo\u003c/i\u003e SVs in a trio context and is robust to offset SV breakpoints. \u003cbr\u003eGrowing SV databases and the increasing availability of SV calls from long-read sequencing make stand-alone genotyping of previously identified SVs an increasingly important component of genome analyses. By treating potential biases as a simulate-able black box NPSV provides a framework for accurately genotyping a broad range of SVs in both targeted and genome-scale applications.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institute of General Medical Sciences","funderIdentifier":"https://doi.org/10.13039/100000057","awardNumber":"P20GM103449"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Heart Lung and Blood Institute","awardNumber":"UM1HL098123"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1827373"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Heart Lung and Blood Institute","awardNumber":"U01HL153009"}],"url":"http://gigadb.org/dataset/100908","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-06-01T09:06:11Z","registered":"2021-06-01T09:06:12Z","published":null,"updated":"2025-05-26T17:15:42Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100905","type":"dois","attributes":{"doi":"10.5524/100905","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Ben","familyName":"Duggan","name":"Duggan, Ben","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1819-2130"}],"affiliation":[]},{"nameType":"Personal","givenName":"John","familyName":"Metzcar","name":"Metzcar, John","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0142-0387"}],"affiliation":[]},{"nameType":"Personal","givenName":"Paul","familyName":"Macklin","name":"Macklin, Paul","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9925-0151"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"DAPT: A package enabling Distributed Automated Parameter Testing\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Workflow","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"model exploration","lang":"en-US"},{"subject":"crowdsourcing","lang":"en-US"},{"subject":"agent-based modeling","lang":"en-US"},{"subject":"workflow","lang":"en-US"},{"subject":"dapt","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-05-25","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.46471/gigabyte.22","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://dapt.readthedocs.io/","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://scicrunch.org/resolver/RRID:SCR_021032","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/BenSDuggan/DAPT","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/PhysiCell-Tools/DAPT-example","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Modern agent-based models (ABM) and other simulation models require evaluation and testing of many different parameters. Managing that testing for large scale parameter sweeps (grid searches) as well as storing simulation data requires multiple, potentially customizable steps that may vary across simulations. Furthermore, parameter testing, processing, and analysis are slowed if simulation and processing jobs cannot be shared across teammates or computational resources. While high-performance computing (HPC) has become increasingly available, models can often be tested faster through the use of multiple computers and HPC resources. To address these issues, we created the Distributed Automated Parameter Testing (DAPT) Python package. By hosting parameters in an online (and often free) \"database\", multiple individuals can run parameter sets simultaneously in a distributed fashion, enabling ad hoc crowdsourcing of computational power. Combining this with a flexible, scriptable tool set, teams can evaluate models and assess their underlying hypotheses quickly. Here we describe DAPT and provide an example demonstrating its use.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1735095"}],"url":"http://gigadb.org/dataset/100905","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-05-25T09:18:34Z","registered":"2021-05-25T09:18:36Z","published":null,"updated":"2025-05-26T17:15:41Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100910","type":"dois","attributes":{"doi":"10.5524/100910","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Eric, 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Jing","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jun","familyName":"Yu","name":"Yu, Jun","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Fabio, Rocha","familyName":"Jimenez Vieira","name":"Jimenez Vieira, Fabio, Rocha","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chris","familyName":"Bowler","name":"Bowler, Chris","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Richard, G","familyName":"Dorrell","name":"Dorrell, Richard, G","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew, A","familyName":"Gitzendanner","name":"Gitzendanner, 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J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Michael, S","familyName":"Barker","name":"Barker, Michael, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"James, H","familyName":"Leebens-Mack","name":"Leebens-Mack, James, H","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Gane, Ka-Shu","familyName":"Wong","name":"Wong, Gane, Ka-Shu","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6108-5560"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Updated data for \"A Phylogenomic View of Evolutionary Complexity in Green Plants\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Transcriptomic","lang":"en-US"},{"subject":"rna","lang":"en-US"},{"subject":"plants","lang":"en-US"},{"subject":"assemblies","lang":"en-US"},{"subject":"genes","lang":"en-US"},{"subject":"contamination","lang":"en-US"},{"subject":"completeness","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-06-30","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJEB4921","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJEB8056","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJEB21674","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/sra?term=SRP012845","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA163187","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Workflow","relatedIdentifierType":"DOI"},{"relationType":"IsNewVersionOf","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The 1000 Plants (1KP) initiative explored the genetic diversity of green plants (Viridiplantae) by sequencing RNA from 1,342 samples representing 1,173 species. All of the analyses done for the 1KP capstone, and previous studies on subsets of these data, are based on a series of de novo transcriptome assemblies and related outputs that will be described in this publication. We also describe assessments of the data quality and an analysis to remove cross-contamination between the samples. These data will be useful to researchers with interests in specific gene families, either across the green plant tree of life or in more focused lineages.\u003cbr\u003e Some samples were not analyzed for the 1KP analysis publication because they were identified as mislabeled and/or contaminated. We released the data nonetheless as some find even these data useful. More information is given at in the original GigaScience datanote, including estimates of which particular sequences might be problematic. \u003cb\u003eIn this updated dataset we have removed the samples and associated files for the 30 specimens where we found significant evidence of mislabeling and/or contamination.\u003c/b\u003e If you require the data from those samples please visit the original dataset 100627.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Alberta Ministry of Advanced Education","awardNumber":"RES0010334"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The National Key Research and Development Program of China"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ministry of Science and Technology of the People's Republic of China","awardNumber":"2015BAD04B01/2015BAD04B03"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ministry of Science and Technology of the People's Republic of China","awardNumber":"2011DQ782025"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Guangdong Province","awardNumber":"2011A091000047"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Shenzhen Municipal Government of China","awardNumber":"CXZZ20140421112021913/ JCYJ20150529150409546/JCYJ20150529150505656"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1265383"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"IOS 0922742"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"IOS-1339156"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"DEB 0830009"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"EF-0629817"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"EF-1550838"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"DEB 0733029"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation Grants","awardNumber":"DBI1062335"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health Grant","awardNumber":"1R01DA025197"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Sciences and Engineering Research Council of Canada","funderIdentifier":"https://doi.org/10.13039/501100000038"}],"url":"http://gigadb.org/dataset/100910","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-06-30T08:05:31Z","registered":"2021-06-30T08:05:33Z","published":null,"updated":"2025-05-26T17:15:41Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100885","type":"dois","attributes":{"doi":"10.5524/100885","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Drew, J","familyName":"Duckett","name":"Duckett, Drew, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2410-3069"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jack","familyName":"Sullivan","name":"Sullivan, Jack","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0216-6867"}],"affiliation":[]},{"nameType":"Personal","givenName":"Stacy","familyName":"Pirro","name":"Pirro, Stacy","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5642-4203"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bryan, C","familyName":"Carstens","name":"Carstens, Bryan, C","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1552-227X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Genomic data for the montane vole (Microtus montanus)"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"genome assembly","lang":"en-US"},{"subject":"mitochondrial genome","lang":"en-US"},{"subject":"illumina sequencing","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-04-14","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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\u003ci\u003eMicrotus\u003c/i\u003e are important research organisms, yet genomic resources in the genus are lacking. Providing such resources would benefit future studies of immunology, phylogeography, cryptic diversity, and more. We sequenced and assembled nuclear genomes from two subspecies of water vole (\u003ci\u003eMicrotus richardsoni\u003c/i\u003e) and from the montane vole (\u003ci\u003eMicrotus montanus\u003c/i\u003e). \u003cbr\u003eThe montane vole is native to the western United States and Canada. Fifteen subspecies of \u003ci\u003eMicrotus montanus\u003c/i\u003e can be found across a range of elevations and habitats, including grasslands, alpine meadows, near stream beds, and close to agricultural land. \u003cbr\u003e\u003ci\u003eMicrotus montanus\u003c/i\u003e sequencing produced over 100M reads and 13x coverage. Preliminary genome assembly resulted in ~13K scaffolds with an N50 of ~3.1Mb, 8.8% Ns, and a BUSCO score of 82.6%. In addition to the nuclear assembly, mitochondrial genome assembly was also performed.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DEB-1457519"},{"funderIdentifierType":"Crossref Funder ID","funderName":"The Ohio State University","awardNumber":"NA"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"DBI-1945347"}],"url":"http://gigadb.org/dataset/100885","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2021-04-14T15:12:37Z","registered":"2021-04-14T15:12:38Z","published":null,"updated":"2025-05-26T17:15:41Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100888","type":"dois","attributes":{"doi":"10.5524/100888","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Guy, M","familyName":"Hagen","name":"Hagen, Guy, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4802-9481"}],"affiliation":[]},{"nameType":"Personal","givenName":"Justin","familyName":"Bendesky","name":"Bendesky, Justin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rosa","familyName":"Machado","name":"Machado, Rosa","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tram-Anh","familyName":"Nguyen","name":"Nguyen, Tram-Anh","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tanmay","familyName":"Kumar","name":"Kumar, Tanmay","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3378-297X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jonathan","familyName":"Ventura","name":"Ventura, Jonathan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-1661-8529"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Fluorescence Microscopy Datasets for Training Deep Neural Networks\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Imaging","lang":"en-US"},{"subject":"fluorescence microscopy","lang":"en-US"},{"subject":"deep learning","lang":"en-US"},{"subject":"convolutional neural networks","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-04-13","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giab032","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Fluorescence microscopy is an important technique in many areas of biological research. Two factors which limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging, and, when imaging live cells, phototoxicity caused by light exposure. Recently developed methods in machine learning are able to greatly improve the signal to noise ratio of acquired images. This allows researchers to record images with much shorter exposure times, which in turn minimizes photobleaching and phototoxicity by reducing the dose of light reaching the sample. To employ deep learning methods, a large amount of data is needed to train the underlying convolutional neural network. One way to do this involves use of pairs of fluorescence microscopy images acquired with long and short exposure times. We provide high quality datasets which can be used to train and evaluate deep learning methods under development. The availability of high quality data is vital for training convolutional neural networks which are used in current machine learning approaches.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"1R15GM128166-01"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Adam, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tabitha, A","familyName":"Hughes","name":"Hughes, Tabitha, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Brock, R","familyName":"McMillan","name":"McMillan, Brock, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9936-9056"}],"affiliation":[]},{"nameType":"Personal","givenName":"Randy, T","familyName":"Larsen","name":"Larsen, Randy, T","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6751-4116"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ruqayya","familyName":"Khan","name":"Khan, Ruqayya","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7549-8761"}],"affiliation":[]},{"nameType":"Personal","givenName":"David","familyName":"Weisz","name":"Weisz, David","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Olga","familyName":"Dudchenko","name":"Dudchenko, Olga","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9163-9544"}],"affiliation":[]},{"nameType":"Personal","givenName":"Erez, Lieberman","familyName":"Aiden","name":"Aiden, Erez, Lieberman","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0634-6486"}],"affiliation":[]},{"nameType":"Personal","givenName":"Nathaniel, B","familyName":"Edelman","name":"Edelman, Nathaniel, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5142-6760"}],"affiliation":[]},{"nameType":"Personal","givenName":"Paul, B","familyName":"Frandsen","name":"Frandsen, Paul, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4801-7579"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"De novo chromosome level assembly of the mule deer (Odocoileus hemionus) genome\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"mule deer","lang":"en-US"},{"subject":"genome","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-11-15","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The mule deer \u003ci\u003eOdocoileus hemionus\u003c/i\u003e is an ungulate species that ranges from western Canada to central Mexico. Mule deer are an essential source of food for many predators, are relatively abundant, and commonly make broad migration movements. A clearer understanding of the mule deer genome can help facilitate knowledge of its population genetics, movements, and demographic history, aiding in conservation efforts. While mule deer are excellent candidates for population genomic studies because of their large population size, continuous distribution, and diversity of habitat, few genomic resources are currently available for this species. Here, we sequence and assemble the mule deer genome into a highly contiguous chromosome-length assembly for use in future research using long-read sequencing and Hi-C. We also provide a genome annotation and compare demographic histories of the mule deer and white-tail deer using PSMC. We expect this assembly to be a valuable resource in the continued study and conservation of mule deer.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Utah Division of Wildlife Resources","awardNumber":"MG19163SS"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"PHY1427654"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Welch Foundation","funderIdentifier":"https://doi.org/10.13039/100000928","awardNumber":"Q-1866"},{"funderIdentifierType":"Crossref Funder ID","funderName":"U.S. Department of Agriculture","funderIdentifier":"https://doi.org/10.13039/100000199","awardNumber":"2017-05741"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of 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G","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2220-797X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Misha","familyName":"Kwasniewski","name":"Kwasniewski, Misha","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3097-9638"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jason, P","familyName":"Londo","name":"Londo, Jason, P","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0535-4820"}],"affiliation":[]},{"nameType":"Personal","givenName":"Qin","familyName":"Ma","name":"Ma, Qin","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3264-8392"}],"affiliation":[]},{"nameType":"Personal","givenName":"Zoë","familyName":"Migicovsky","name":"Migicovsky, Zoë","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3931-1258"}],"affiliation":[]},{"nameType":"Personal","givenName":"Joel, F","familyName":"Swift","name":"Swift, Joel, F","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7186-3298"}],"affiliation":[]},{"nameType":"Personal","givenName":"Allison, J","familyName":"Miller","name":"Miller, Allison, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2722-9361"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Multi-dimensional leaf phenotypes reflect root system genotype in grafted grapevine over the growing season\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2021,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"Phenotyping","lang":"en-US"},{"subject":"Metabolomic","lang":"en-US"},{"subject":"Imaging","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"grapevine","lang":"en-US"},{"subject":"phenomics","lang":"en-US"},{"subject":"gene expression","lang":"en-US"},{"subject":"metabolomics","lang":"en-US"},{"subject":"ionomics","lang":"en-US"},{"subject":"morphology","lang":"en-US"}],"contributors":[],"dates":[{"date":"2021-12-29","dateType":"Available"},{"date":"2021","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Modern biological approaches generate volumes of multi-dimensional data, offering unprecedented opportunities to address biological questions previously beyond reach due to small or subtle effects. A fundamental question in plant biology is the extent to which below-ground activity in the root system influences above-ground phenotypes expressed in the shoot system. Grafting, an ancient horticultural practice that fuses the root system of one individual (the rootstock) with the shoot system of a second, genetically distinct individual (the scion), is a powerful experimental system to understand below-ground effects on above-ground phenotypes. Previous studies on grafted grapevines have detected rootstock influence on scion phenotypes including physiology and berry chemistry. However, the extent of the rootstocks influence on leaves, the photosynthetic engines of the vine, and how those effects change over the course of a growing season, are still largely unknown.\u003cbr\u003eHere, we investigate associations between rootstock genotype and shoot system phenotypes using five multi-dimensional leaf phenotyping modalities measured in a common grafted scion: ionomics, metabolomics, transcriptomics, morphometrics, and physiology. Rootstock influence is ubiquitous but subtle across modalities with the strongest signature of rootstock observed in the leaf ionome. Moreover, we find that the extent of rootstock influence on scion phenotypes and patterns of phenomic covariation are highly dynamic across the season.\u003cbr\u003eThese findings substantially expand previously identified patterns to demonstrate that rootstock influence on scion phenotypes is complex and dynamic and underscore that broad understanding necessitates volumes of multi-dimensional data previously unmet.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1546869"}],"url":"http://gigadb.org/dataset/100956","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":5,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2022-01-07T16:23:35Z","registered":"2022-01-07T16:23:36Z","published":null,"updated":"2025-05-26T17:15:34Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/100963","type":"dois","attributes":{"doi":"10.5524/100963","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Niema","familyName":"Moshiri","name":"Moshiri, Niema","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-2209-8128"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"NiemaGraphGen: A memory-efficient global-scale contact network simulation toolkit\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2022,"subjects":[{"subject":"Network-Analysis","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"software","lang":"en-US"},{"subject":"contact network","lang":"en-US"},{"subject":"simulation","lang":"en-US"},{"subject":"epidemiology","lang":"en-US"}],"contributors":[],"dates":[{"date":"2022-01-19","dateType":"Available"},{"date":"2022","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.46471/gigabyte.37","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://hub.docker.com/r/niemasd/niemagraphgen","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"\u003cscript src=\"https://codeocean.com/widget.js?slug=7496582\" async\u003e\u003c/script\u003e","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/niemasd/NiemaGraphGen","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/niemasd/NiemaGraphGen-Paper","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Epidemic simulations require the ability to sample contact networks from various random graph models. Existing methods can simulate city-scale or even country-scale contact networks, but they are unable to feasibly simulate global-scale contact networks due to high memory consumption. \u003cbr\u003eNiemaGraphGen (NGG) is a memory-efficient graph generation tool that enables the simulation of global-scale contact networks. NGG avoids storing the entire graph in memory and is instead intended to be used in a data streaming pipeline, resulting in memory consumption that is orders of magnitude smaller than existing tools. \u003cbr\u003eNGG provides a massively-scalable solution for simulating social contact networks, enabling global-scale epidemic simulation studies.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"NSF-2028040"}],"url":"http://gigadb.org/dataset/100963","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2022-01-19T17:16:36Z","registered":"2022-01-19T17:16:38Z","published":null,"updated":"2025-05-26T17:15:34Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102233","type":"dois","attributes":{"doi":"10.5524/102233","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Haolong","familyName":"Wang","name":"Wang, Haolong","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3830-7799"}],"affiliation":[]},{"nameType":"Personal","givenName":"Baofeng","familyName":"Su","name":"Su, Baofeng","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9633-2733"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ian, AE","familyName":"Butts","name":"Butts, Ian, AE","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1591-6471"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rex, A","familyName":"Dunham","name":"Dunham, Rex, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-6149-6017"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xu","familyName":"Wang","name":"Wang, Xu","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7594-5004"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Chromosome-level assembly and annotation of the blue catfish \u003ci\u003eIctalurus furcatus\u003c/i\u003e, an aquaculture species for hybrid catfish reproduction, epigenetics, and heterosis studies\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2022,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"blue catfish","lang":"en-US"},{"subject":"chromosomal assembly","lang":"en-US"},{"subject":"channel catfish","lang":"en-US"},{"subject":"heterosis","lang":"en-US"},{"subject":"epigenetics","lang":"en-US"},{"subject":"linked-reads technology","lang":"en-US"},{"subject":"pacbio sequencing","lang":"en-US"}],"contributors":[],"dates":[{"date":"2022-06-23","dateType":"Available"},{"date":"2022","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giac070","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA785621","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The blue catfish is of great value in aquaculture and recreational fisheries. The F1 hybrids of female channel catfish (\u003ci\u003eIctalurus punctatus\u003c/i\u003e) x male blue catfish (\u003ci\u003eI. furcatus\u003c/i\u003e) have been the primary driver of US catfish production in recent years because of superior growth, survival, and carcass yield. The channel-blue hybrid also provides an excellent model to investigate molecular mechanisms of environment-dependent heterosis. However, transcriptome and methylome studies suffered from low alignment rates to the channel catfish genome due to divergence, and the genome resources for blue catfish are not publicly available. \u003cbr\u003eThe blue catfish genome assembly is 841.86 Mbp in length with excellent continuity (8.6 Mbp contig N50, 28.2 Mbp scaffold N50) and completeness (98.6% BUSCO). A total of 30,971 protein-coding genes were predicted, of which 21,781 were supported by RNA-seq evidence. Phylogenomic analyses revealed that it diverged from channel catfish approximately 9 million years ago with 15.7 million fixed nucleotide differences. The within-species SNP density is 0.32% between the most agriculturally important blue catfish strains (D\u0026amp;B and Rio Grande). Gene family analysis discovered significant expansion of immune-related families in the blue catfish lineage, which may contribute to disease resistance in blue catfish. \u003cbr\u003eWe reported the first high-quality, chromosome-level assembly of the blue catfish genome, which provides the necessary genomic tool kit for transcriptome and methylome analysis, SNP discovery and marker-assisted selection, gene editing and genome engineering, as well as reproductive enhancement of the blue catfish and hybrid catfish.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"USDA","awardNumber":"1018100"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Alabama Agriculture Experiment Station (AAES) Agriculture Research Enhancement"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Auburn University College Veterinary Medicine"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Auburn 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C","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4410-9679"}],"affiliation":[]},{"nameType":"Personal","givenName":"Hongyu","familyName":"Jin","name":"Jin, Hongyu","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4562-0639"}],"affiliation":[]},{"nameType":"Personal","givenName":"Christine","familyName":"Smith","name":"Smith, Christine","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8128-2924"}],"affiliation":[]},{"nameType":"Personal","givenName":"Linsey","familyName":"Newton","name":"Newton, Linsey","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7149-4752"}],"affiliation":[]},{"nameType":"Personal","givenName":"Carson, M","familyName":"Andorf","name":"Andorf, 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Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data -- 18M markers -- from two partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least seven US states and scored for 162 distinct trait datasets enabled the identification of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be three genes based a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g. above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype by environment interaction.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Advanced Research Projects Agency-Energy","awardNumber":"DE-AR0001064"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Advanced Research Projects Agency-Energy","awardNumber":"DE-AR0001367"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"OIA-1557417"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Wanying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5845-0018"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wen","familyName":"Wang","name":"Wang, Wen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7801-2066"}],"affiliation":[]},{"nameType":"Personal","givenName":"Qianghua","familyName":"Xu","name":"Xu, Qianghua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0351-1765"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chi-Hing, Christina","familyName":"Cheng","name":"Cheng, Chi-Hing, Christina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6308-8685"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"The genome and transcriptome of the Antarctic toothfish Dissostichus mawsoni"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{"identifier":"100545","identifierType":"DOI","type":"DataRepository"},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"adaptive radiation","lang":"en-US"},{"subject":"climate change","lang":"en-US"},{"subject":"genome","lang":"en-US"},{"subject":"oxidative stress","lang":"en-US"},{"subject":"antarctic notothenioids","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-01-18","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz016","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA401363","relatedIdentifierType":"URL"},{"relationType":"IsPartOf","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["45.37 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The Antarctic toothfish \u003ci\u003eDissostichus mawsoni\u003c/i\u003e can grow to giant sizes (2.0 m in length and 140 kg in mass) and is an iconic species of the Antarctic notothenioid radiation, with wide distributions in freezing waters of high latitude Antarctic coasts, as far south as 77.5o 107 S, the southern limit of Antarctic marine life. It thus exemplifies the stenothermal cold-adapted character state. Despite its large size, it is the only notothenioid species that achieved complete neutral buoyancy as adults; thus this species serves as the best model for examining the evolutionary underpinning of secondary pelagicism in the Antarctic clade. \u003cbr\u003e Here we provide the chromosome-level genome assembly of \u003ci\u003eD.mawsoni\u003c/i\u003e using the Illumina, PacBio, and Hi-C sequencing data. A total of ~107Gb of raw data covering the predicted genome length ~840Mb to ~ 139× read depth. The de novo genome assembly of ~757 Mb generated a scaffold N50 of ~2.2Mb with 22,516 intact predicted protein-coding gene models. BUSCO evaluation demonstrated that the genome completeness reached 97.2%. Additionally we demonstrat expression profiles and sequence variations with RNA seq data from 13 tissues (liver, gill, stomach, white muscle, red muscle, skin, small intestine, brain, head kidney, caudal kidney, spleen, and ovary ).","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"41761134050"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572611"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572598"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Shanghai Education Committee","awardNumber":"2017-01-07-00-10-E00060"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"ANT1142158"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Laboratory for Marine Biology \u0026 Biotechnology Qingdao National Laboratory for Marine Science \u0026 Technology","awardNumber":"2017-2018"}],"url":"http://gigadb.org/dataset/102162","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-01-18T19:19:39Z","registered":"2019-01-18T19:19:40Z","published":null,"updated":"2025-05-26T17:04:17Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102163","type":"dois","attributes":{"doi":"10.5524/102163","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Liangbiao","familyName":"Chen","name":"Chen, Liangbiao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0717-8536"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ying","familyName":"Lu","name":"Lu, Ying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wenhao","familyName":"Li","name":"Li, Wenhao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yandong","familyName":"Ren","name":"Ren, Yandong","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mengchao","familyName":"Yu","name":"Yu, Mengchao","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Shouwen","familyName":"Jiang","name":"Jiang, Shouwen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Yanxia","familyName":"Fu","name":"Fu, Yanxia","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jian","familyName":"Wang","name":"Wang, Jian","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Sihua","familyName":"Peng","name":"Peng, Sihua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Kevin, T","familyName":"Bilyk","name":"Bilyk, Kevin, T","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2262-2703"}],"affiliation":[]},{"nameType":"Personal","givenName":"Katherine, R","familyName":"Murphy","name":"Murphy, Katherine, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8898-8719"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xuan","familyName":"Zhuang","name":"Zhuang, Xuan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mathias","familyName":"Hune","name":"Hune, Mathias","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wanying","familyName":"Zhai","name":"Zhai, Wanying","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wen","familyName":"Wang","name":"Wang, Wen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Qianghua","familyName":"Xu","name":"Xu, Qianghua","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Chi-Hing, Christina","familyName":"Cheng","name":"Cheng, Chi-Hing, Christina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"The genome and transcriptome of the Patagonia robalo Eleginops maclovinus"}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{"identifier":"100545","identifierType":"DOI","type":"DataRepository"},"publicationYear":2019,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"adaptive radiation","lang":"en-US"},{"subject":"climate change","lang":"en-US"},{"subject":"genome","lang":"en-US"},{"subject":"oxidative stress","lang":"en-US"},{"subject":"antarctic notothenioids","lang":"en-US"}],"contributors":[],"dates":[{"date":"2019-01-18","dateType":"Available"},{"date":"2019","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giz016","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA401363","relatedIdentifierType":"URL"},{"relationType":"IsPartOf","resourceTypeGeneral":"Other","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["43.78 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"\u003ci\u003eEleginops maclovinus\u003c/i\u003e, the Patagonian robalo, is a species of notothenioid fish found in coastal and estuarine habitats around southernmost South America, ranging as far north as Valparaíso on the Pacific side, and Uruguay on the Atlantic side. It is the only member of its genus, which is the only member of the family Eleginopsidae. It is an omnivore, tending towards carnivore. In some parts of its range, it is especially fond of Paracorophium, but it is opportunistic, and its exact diet depends on the availability in the habitat where the individual fish lives. It reaches about 105 cm (3.44 ft) in length, and can live for 10 years. It is a protandric hermaphrodite, and males predominate in lengths below 52 cm (1.71 ft), while female predominate above.\u003cbr\u003e Here we provide the chromosome-level genome assembly of \u003ci\u003eE. maclovinus\u003c/i\u003e using the Illumina, PacBio, and Hi-C sequencing data. A total of ~411Gb of raw data covering the predicted genome length ~780Mb to ~ 590× read depth. The de novo genome assembly of ~727 Mb generated a scaffold N50 of ~0.69 Mb with 22,959 intact predicted protein-coding gene models. BUSCO evaluation demonstrated that the genome completeness reached 95.0%. Additionally we demonstrat expression profiles and sequence variations with RNA seq data from 13 tissues (liver, gill, stomach, white muscle, red muscle, skin, small intestine, brain, head kidney, caudal kidney, spleen, and ovary ).","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"41761134050"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572611"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Natural Science Foundation of China","awardNumber":"31572598"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Shanghai Education Committee","awardNumber":"2017-01-07-00-10-E00060"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"ANT1142158"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Key Achievement Supporting Grant from Laboratory for Marine Biology \u0026 Biotechnology","awardNumber":"Qingdao National Laboratory for Marine Science \u0026 Technology"}],"url":"http://gigadb.org/dataset/102163","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2019-01-21T03:44:48Z","registered":"2019-01-21T03:44:49Z","published":null,"updated":"2025-05-26T17:04:17Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102197","type":"dois","attributes":{"doi":"10.5524/102197","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Simone","familyName":"Marini","name":"Marini, Simone","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5704-3533"}],"affiliation":[]},{"nameType":"Personal","givenName":"Marco","familyName":"Oliva","name":"Oliva, Marco","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0525-3114"}],"affiliation":[]},{"nameType":"Personal","givenName":"Ilya, B","familyName":"Slizovskiy","name":"Slizovskiy, Ilya, B","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0758-5510"}],"affiliation":[]},{"nameType":"Personal","givenName":"Rishabh, A","familyName":"Das","name":"Das, Rishabh, A","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Noelle, R","familyName":"Noyes","name":"Noyes, Noelle, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-6149-1008"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tamer","familyName":"Kahveci","name":"Kahveci, Tamer","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Christina","familyName":"Boucher","name":"Boucher, Christina","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9509-9725"}],"affiliation":[]},{"nameType":"Personal","givenName":"Mattia","familyName":"Prosperi","name":"Prosperi, Mattia","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9021-5595"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"AMR-meta: ak-mer and metafeature approach to classify antimicrobial resistance from high-throughput short-read metagenomics data\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2022,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"Metagenomic","lang":"en-US"},{"subject":"functional metagenomics","lang":"en-US"},{"subject":"short reads","lang":"en-US"},{"subject":"antimicrobial resistance","lang":"en-US"},{"subject":"machine learning","lang":"en-US"},{"subject":"matrix factorization","lang":"en-US"}],"contributors":[],"dates":[{"date":"2022-02-17","dateType":"Available"},{"date":"2022","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giac029","relatedIdentifierType":"DOI"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/smarini/AMR-meta","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Antimicrobial resistance (AMR) is a global health concern. High-throughput metagenomic sequencing of microbial samples enables profiling of AMR genes through comparison with curated AMR databases. However, performance of current methods are often hampered by database incompleteness, and presence of homology/homoplasy with other non-AMR genes in sequenced samples. \u003cbr\u003eWe present AMR-meta, a database-free and alignment-free approach, based on k-mers, which combines algebraic matrix factorization into metafeatures with regularized regression. Metafeatures capture multi-level gene diversity across main antibiotic classes. AMR-meta takes in reads from metagenomic shotgun sequencing and outputs predictions about whether those reads contribute to resistance against specific classes of antibiotics. In addition, AMR-meta employs an augmented training strategy that joins an AMR gene database with non-AMR genes (used as negative examples). We compare AMR-meta with AMRPlusPlus, DeepARG, and Meta-MARC, further testing their ensemble via a voting system. In cross-validation, AMR-meta has a median (interquartile) f-score of 0.7 (0.2-0.9). On semi-synthetic metagenomic data external test on average AMR-meta yields a 1.3-fold hit rate increase over existing methods. In terms of run-time, AMR-meta is 3x faster than DeepARG and 30x faster than Meta-MARC, and as fast as AMRPlusPlus. Finally, we note that differences in AMR ontologies and observed variance of all tools in classification outputs call for further development on standardization of benchmarking data and protocols. \u003cbr\u003eAMR-meta is a fast, accurate classifier that exploits non-AMR negative sets to improve sensitivity and specificity. The differences in AMR ontologies and the high variance of all tools in classification outputs call for the deployment of standard benchmarking data and protocols, to fairly compare AMR prediction tools.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Institutes of Health","funderIdentifier":"https://doi.org/10.13039/100000002","awardNumber":"R01AI141810"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"2013998"},{"funderIdentifierType":"Crossref Funder ID","funderName":"United States Department of Agriculture","awardNumber":"2019-67017-29110"}],"url":"http://gigadb.org/dataset/102197","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2022-02-17T15:00:52Z","registered":"2022-02-17T15:00:54Z","published":null,"updated":"2025-05-26T17:04:10Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102258","type":"dois","attributes":{"doi":"10.5524/102258","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Dylan, L","familyName":"Schultz","name":"Schultz, Dylan, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-3684-7062"}],"affiliation":[]},{"nameType":"Personal","givenName":"Evelyne","familyName":"Selberherr","name":"Selberherr, Evelyne","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2253-5247"}],"affiliation":[]},{"nameType":"Personal","givenName":"Corinne, M","familyName":"Stouthamer","name":"Stouthamer, Corinne, M","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-7561-8847"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew, R","familyName":"Doremus","name":"Doremus, Matthew, R","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1672-560X"}],"affiliation":[]},{"nameType":"Personal","givenName":"Suzanne, E","familyName":"Kelly","name":"Kelly, Suzanne, E","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-5515-1741"}],"affiliation":[]},{"nameType":"Personal","givenName":"Martha, S","familyName":"Hunter","name":"Hunter, Martha, S","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Stephan","familyName":"Schmitz-Esser","name":"Schmitz-Esser, Stephan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1907-0709"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Sex-based \u003ci\u003ede novo\u003c/i\u003e transcriptome assemblies of the parasitoid wasp \u003ci\u003eEncarsia suzannae\u003c/i\u003e, a host of the manipulative heritable symbiont \u003ci\u003eCardinium hertigii\u003c/i\u003e\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2022,"subjects":[{"subject":"Transcriptomic","lang":"en-US"},{"subject":"encarsia","lang":"en-US"},{"subject":"parasitoid wasp","lang":"en-US"},{"subject":"cytoplasmic incompatibility","lang":"en-US"},{"subject":"transcriptome","lang":"en-US"},{"subject":"cardinium","lang":"en-US"}],"contributors":[],"dates":[{"date":"2022-08-24","dateType":"Available"},{"date":"2022","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.46471/gigabyte.68","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA737477","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA737478","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Minute parasitoid wasps in the genus \u003ci\u003eEncarsia\u003c/i\u003e are commonly used as biological pest control agents of whiteflies and armored scale insects in greenhouses or in the field. They are also a key host of the bacterial endosymbiont \u003ci\u003eCardinium hertigii\u003c/i\u003e which can cause a suite of reproductive manipulation phenotypes, including parthenogenesis, feminization, and cytoplasmic incompatibility; the last being most thoroughly studied in \u003ci\u003eEncarsia suzannae\u003c/i\u003e. Despite their biological and economic importance, there are currently no published \u003ci\u003eEncarsia\u003c/i\u003e genomes and only one public transcriptome. In this study, we applied a mapping-and-removal approach to eliminate known contaminants from previously-obtained Illumina sequencing data. We generated \u003ci\u003ede novo\u003c/i\u003e transcriptome assemblies for both female and male \u003ci\u003eE. suzannae\u003c/i\u003e which contain 45,986 and 54,762 final coding sequences, respectively. Benchmarking Single-Copy Orthologs (BUSCO) results indicate both assemblies are highly complete. Preliminary analyses revealed the presence of homologs of sex-determination genes characterized in other insects and putative venom proteins. These transcriptomes will be valuable tools to better understand the biology of \u003ci\u003eEncarsia\u003c/i\u003e wasps and their evolutionary relatives. Furthermore, the separate male and female assemblies will be particularly useful references for studies involving insects of only one sex.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"IOS-2002987"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Members of this genus are distributed worldwide and therefore of broad scientific and ecological importance. For \u003ci\u003ePoc. acuta\u003c/i\u003e, a high-quality assembly was generated using short-read Illumina and long-read PacBio data. The \u003ci\u003ePoc. acuta\u003c/i\u003e assembly is from a triploid individual, making it the first reference genome of a non-diploid coral animal. This genome assembly is a significant improvement over available data and provides an invaluable resource for supporting multi-omics studies into coral biology, not just in Hawaii, but also in other regions, where related species exist. The \u003ci\u003ePoc. acuta\u003c/i\u003e assembly gives us, for the first time, a platform for studying polyploidy in corals, and its role in genome evolution and stress adaptation in these organisms.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Paul G. 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Members of this genus are distributed worldwide and therefore of broad scientific and ecological importance. For \u003ci\u003ePoc. meandrina\u003c/i\u003e, a high-quality assembly was generated using short-read Illumina and long-read PacBio data. This genome assembly is a significant improvement over available data and provides an invaluable resource for supporting multi-omics studies into coral biology, not just in Hawaii, but also in other regions, where related species exist.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Paul G. 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A recent surge in computational methods that aim to accurately estimate taxonomic profiles, called taxonomic profilers, have motivated community driven efforts to create standardized benchmarking datasets and platforms, standardized taxonomic profile formats, as well as a benchmarking platform to assess tool performance. While this standardization is essential, there is currently a lack of tools to visualize the standardized output of the many existing taxonomic profilers. Thus, benchmarking studies rely on a single value metrics to compare performance of tools and compare to benchmarking datasets. This is one of the major problems in analyzing metagenomic profiling data, since single metrics, such as the F1 score, fail to capture the biological differences between the datasets. \u003cbr\u003eHere we report the development of TAMPA (Taxonomic metagenome profiling evaluation) , a robust and easy-to-use method that allows scientists to easily interpret and interact with taxonomic profiles produced by the many different taxonomic profiler methods beyond the standard metrics used by the scientific community. We demonstrate the unique ability of TAMPA to generate novel biological hypothesis by highlighting the taxonomic differences between samples otherwise missed by commonly utilized metrics. \u003cbr\u003e In this study, we show that TAMPA can help visualize the output of taxonomic profilers, enabling biologists to effectively choose the most appropriate profiling method to use on their metagenomics data. TAMPA is available on GitHub, Bioconda and Galaxy Toolshed at https://github.com/dkoslicki/TAMPA, and is released under the MIT license.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"2041984"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"2135954"}],"url":"http://gigadb.org/dataset/102350","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-01-28T13:05:40Z","registered":"2023-01-28T13:05:41Z","published":null,"updated":"2025-05-26T17:03:49Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102404","type":"dois","attributes":{"doi":"10.5524/102404","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Chunyu","familyName":"Ma","name":"Ma, Chunyu","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9731-5153"}],"affiliation":[]},{"nameType":"Personal","givenName":"Zhihan","familyName":"Zhou","name":"Zhou, Zhihan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-1473-9071"}],"affiliation":[]},{"nameType":"Personal","givenName":"Han","familyName":"Liu","name":"Liu, Han","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"David","familyName":"Koslicki","name":"Koslicki, David","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0640-954X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"KGML-xDTD: A Knowledge Graph-based Machine Learning Framework for Drug Treatment Prediction and Mechanism Description\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2023,"subjects":[{"subject":"Metadata","lang":"en-US"},{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Software","lang":"en-US"},{"subject":"drug repurposing","lang":"en-US"},{"subject":"reinforcement learning","lang":"en-US"},{"subject":"biomedical knowledge graph","lang":"en-US"}],"contributors":[],"dates":[{"date":"2023-06-09","dateType":"Available"},{"date":"2023","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giad057","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://doi.org/10.5281/zenodo.7582233","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://registry.dome-ml.org/review/zg83kd0vmv","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/chunyuma/KGML-xDTD","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings. \u003cbr\u003eIn this work, we propose KGML-xDTD: a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a two-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable mechanisms of action (MOAs). We leverage knowledge-and-publication based information to extract biologically meaningful \"demonstration paths\" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths. \u003cbr\u003e KGML-xDTD is the first model framework that can offer KG-path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce \"black-box\" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations, and further accelerate the process of drug discovery for emerging diseases.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Center for Advancing Translational Sciences","funderIdentifier":"https://doi.org/10.13039/100006108","awardNumber":"OT2-TR003428-01S3"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Center for Advancing Translational Sciences","funderIdentifier":"https://doi.org/10.13039/100006108","awardNumber":"OT2-TR003428-01S2"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Center for Advancing Translational Sciences","funderIdentifier":"https://doi.org/10.13039/100006108","awardNumber":"OT2-TR003428-01"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science 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Sagar","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4896-2658"}],"affiliation":[]},{"nameType":"Personal","givenName":"Zachary, N","familyName":"Harris","name":"Harris, Zachary, N","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8299-3074"}],"affiliation":[]},{"nameType":"Personal","givenName":"Jason, P","familyName":"Londo","name":"Londo, Jason, P","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0535-4820"}],"affiliation":[]},{"nameType":"Personal","givenName":"Allison, J","familyName":"Miller","name":"Miller, Allison, J","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-2722-9361"}],"affiliation":[]},{"nameType":"Personal","givenName":"Anne","familyName":"Fennell","name":"Fennell, Anne","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4234-6419"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Genome assembly of the hybrid grapevine \u003ci\u003eVitis\u003c/i\u003e ‘Chambourcin’\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2023,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Transcriptomic","lang":"en-US"},{"subject":"vitis ‘chambourcin’","lang":"en-US"},{"subject":"grape genome","lang":"en-US"},{"subject":"hybrid assembly: wine","lang":"en-US"},{"subject":"pacbio hifi","lang":"en-US"},{"subject":"bionano","lang":"en-US"}],"contributors":[],"dates":[{"date":"2023-06-29","dateType":"Available"},{"date":"2023","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.46471/gigabyte.84","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Dataset","relatedIdentifier":"http://www.ncbi.nlm.nih.gov/bioproject/PRJNA754438","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://doi.org/10.6084/m9.figshare.15505788.v1","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 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Few genomic resources are available for hybrid grapevines like Chambourcin. Here, we assembled the genome of Chambourcin using PacBio HiFi long-read, Bionano optical map, and Illumina short-read sequencing technologies. We generated an assembly for Chambourcin with 26 scaffolds, with an N50 length of 23.3 Mb and an estimated BUSCO completeness of 97.9%. We predicted 33,791 gene models and identified 16,056 common orthologs between Chambourcin, \u003ci\u003eV. vinifera\u003c/i\u003e PN40024 12X.v2, VCOST.v3, Shine Muscat and \u003ci\u003eV. riparia\u003c/i\u003e Gloire. We found 1,606 plant transcription factors from 58 gene families. Finally, we identified 304,571 simple sequence repeats (up to six base pairs long). Our work provides the genome assembly, annotation and the protein and coding sequences of Chambourcin. Our genome assembly is a valuable resource for genome comparisons, functional genomic analyses and genome-assisted breeding research.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"1546869"}],"url":"http://gigadb.org/dataset/102415","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-06-29T10:11:03Z","registered":"2023-06-29T10:11:04Z","published":null,"updated":"2025-05-26T16:58:53Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102419","type":"dois","attributes":{"doi":"10.5524/102419","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Kai","familyName":"Blumberg","name":"Blumberg, Kai","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3410-4655"}],"affiliation":[]},{"nameType":"Personal","givenName":"Matthew","familyName":"Miller","name":"Miller, Matthew","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3491-8763"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alise","familyName":"Ponsero","name":"Ponsero, Alise","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-4125-7561"}],"affiliation":[]},{"nameType":"Personal","givenName":"Bonnie, L","familyName":"Hurwitz","name":"Hurwitz, Bonnie, L","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-8699-957X"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Ontology-Driven Analysis of Marine Metagenomics: What More Can We Learn from Our Data?\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2023,"subjects":[{"subject":"Software","lang":"en-US"},{"subject":"Metagenomic","lang":"en-US"},{"subject":"ontology","lang":"en-US"},{"subject":"metagenomics","lang":"en-US"},{"subject":"microbial ecology","lang":"en-US"},{"subject":"rdf","lang":"en-US"},{"subject":"fair data","lang":"en-US"}],"contributors":[],"dates":[{"date":"2023-08-04","dateType":"Available"},{"date":"2023","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB Dataset"},"relatedIdentifiers":[{"relationType":"IsCitedBy","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"10.1093/gigascience/giad088","relatedIdentifierType":"DOI"},{"relationType":"References","resourceTypeGeneral":"Other","relatedIdentifier":"https://doi.org/10.5281/zenodo.7732330","relatedIdentifierType":"URL"},{"relationType":"References","resourceTypeGeneral":"Workflow","relatedIdentifierType":"DOI"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/hurwitzlab/planet-microbe-semantic-web-analysis","relatedIdentifierType":"URL"},{"relationType":"HasPart","resourceTypeGeneral":"Software","relatedIdentifier":"https://github.com/hurwitzlab/planet-microbe-functional-annotation/","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":["1 GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The proliferation of metagenomic sequencing technologies have enabled novel insights into the functional genomic potentials and taxonomic structure of microbial communities. However, cyberinfrastructure efforts to manage and enable the reproducible analysis of sequence data have not kept pace. Thus, there is increasing recognition of the need to make metagenomic data discoverable within machine searchable frameworks compliant with the FAIR principles for data stewardship. Although a variety of metagenomic web services exist, none currently leverage the hierarchically structured terminology encoded within common life-science ontologies to programmatically discover data. Here, we integrate large-scale marine metagenomic datasets with community-driven life-science ontologies into a novel FAIR web service. This approach enables the retrieval of data discovered by intersecting the knowledge represented within ontologies against the functional genomic potential and taxonomic structure computed from marine sequencing data. Our findings highlight various microbial functional and taxonomic patterns relevant to the ecology of prokaryotes in various aquatic environments. Most importantly, we present and evaluate a novel web service accessible through an open API that can be used to ask novel biological questions of existing metagenomic datasets. Finally, the FAIR ontology searchable data products provided by our API can be leveraged by future research efforts.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Academy of Finland","awardNumber":"339172"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"OCE-1639614"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"CISE-1640775"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Simons Foundation","funderIdentifier":"https://doi.org/10.13039/100000893","awardNumber":"481471"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Gordon and Betty Moore Foundation","funderIdentifier":"https://doi.org/10.13039/100000936","awardNumber":"GBMF 8751"}],"url":"http://gigadb.org/dataset/102419","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":1,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-08-02T01:38:39Z","registered":"2023-08-02T01:38:40Z","published":null,"updated":"2025-05-26T16:58:53Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102487","type":"dois","attributes":{"doi":"10.5524/102487","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Pedro, Gabriel","familyName":"Nachtigall","name":"Nachtigall, Pedro, Gabriel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-3196-0173"}],"affiliation":[]},{"nameType":"Personal","givenName":"Alan, Mitchell","familyName":"Durham","name":"Durham, Alan, Mitchell","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-9846-6911"}],"affiliation":[]},{"nameType":"Personal","givenName":"Darin, R.","familyName":"Rokyta","name":"Rokyta, Darin, R.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0356-2178"}],"affiliation":[]},{"nameType":"Personal","givenName":"Inácio, L.M.","familyName":"Junqueira-de-Azevedo","name":"Junqueira-de-Azevedo, Inácio, L.M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-4491-0180"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"ToxCodAn-Genome: an automated pipeline for toxin-gene annotation in genome assembly of venomous lineages\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2023,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Software","lang":"en-US"},{"subject":"genome annotation","lang":"en-US"},{"subject":"gene model","lang":"en-US"},{"subject":"venomics","lang":"en-US"},{"subject":"wgs","lang":"en-US"},{"subject":"dna-seq","lang":"en-US"}],"contributors":[],"dates":[{"date":"2023-12-14","dateType":"Available"},{"date":"2023","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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GB"],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","lang":"en","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The rapid development of sequencing technologies resulted in a wide expansion of genomics studies using venomous lineages. This facilitated research focusing on understanding the evolution of adaptive traits and the search for novel compounds that can be applied in agriculture and medicine. However, the toxin annotation of genomes is a laborious and time-consuming task, and no consensus pipeline is currently available. No computational tool currently exists to address the challenges specific to toxin annotation and to ensure the reproducibility of the process. Here, we present ToxCodAn-Genome, the first software designed to perform automated toxin annotation in genomes of venomous lineages. This pipeline was designed to retrieve the full-length coding sequences of toxins and to allow the detection of novel truncated paralogs and pseudogenes. We tested ToxCodAn-Genome using 12 genomes of venomous lineages and achieved high performance on recovering their current toxin annotations. This tool can be easily customized to allow improvements in the final toxin annotation set and can be expanded to virtually any venomous lineage. ToxCodAn-Genome is fast, allowing it to run on any personal computer, but it can also be executed in multi-core mode, taking advantage of large high-performance servers. In addition, we provide a guide to direct future research in the venomics field to ensure a confident toxin annotation in the genome being studied. As a case study, we sequenced and annotated the toxin repertoire of \u003ci\u003eBothrops alternatus\u003c/i\u003e, which may facilitate future evolutionary and biomedical studies using vipers as models.ToxCodAn-Genome and the guide are freely available at https://github.com/pedronachtigall/ToxCodAn-Genome.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"Fundação de Amparo à Pesquisa do Estado de São Paulo","awardNumber":"2018/26520-4"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Fundação de Amparo à Pesquisa do Estado de São Paulo","awardNumber":"2016/50127-5"},{"funderIdentifierType":"Crossref Funder ID","funderName":"Fundação de Amparo à Pesquisa do Estado de São Paulo","awardNumber":"2022/04988-0"},{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"NSF DEB 1638902"}],"url":"http://gigadb.org/dataset/102487","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":4,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2023-12-14T03:55:04Z","registered":"2023-12-14T03:55:05Z","published":null,"updated":"2025-05-26T16:58:46Z"},"relationships":{"client":{"data":{"id":"cngb.gigadb","type":"clients"}}}},{"id":"10.5524/102504","type":"dois","attributes":{"doi":"10.5524/102504","identifiers":[],"creators":[{"nameType":"Personal","givenName":"Yiyan","familyName":"Yang","name":"Yang, Yiyan","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9508-7396"}],"affiliation":[]},{"nameType":"Personal","givenName":"Keith","familyName":"Dufault-Thompson","name":"Dufault-Thompson, Keith","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0991-2255"}],"affiliation":[]},{"nameType":"Personal","givenName":"Wei","familyName":"Yan","name":"Yan, Wei","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-5271-1515"}],"affiliation":[]},{"nameType":"Personal","givenName":"Tian","familyName":"Cai","name":"Cai, Tian","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org"}],"affiliation":[]},{"nameType":"Personal","givenName":"Lei","familyName":"Xie","name":"Xie, Lei","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9051-2111"}],"affiliation":[]},{"nameType":"Personal","givenName":"Xiaofang","familyName":"Jiang","name":"Jiang, Xiaofang","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0002-0955-8284"}],"affiliation":[]}],"titles":[{"lang":"en-US","title":"Supporting data for \"Large-scale Genomic Survey with Deep Learning-based Method Reveals Strain-Level Phage Specificity Determinants\""}],"publisher":{"publisherIdentifierScheme":"re3data","schemeUri":"https://www.re3data.org/","name":"GigaScience Database","lang":"en-US","publisherIdentifier":"http://doi.org/10.17616/R3TG83"},"container":{},"publicationYear":2024,"subjects":[{"subject":"Genomic","lang":"en-US"},{"subject":"Bioinformatics","lang":"en-US"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Software","lang":"en-US"},{"subject":"phage-host specificity","lang":"en-US"},{"subject":"phage receptor-binding protein","lang":"en-US"},{"subject":"bacterial polysaccharide","lang":"en-US"},{"subject":"serotype","lang":"en-US"},{"subject":"phage therapy","lang":"en-US"}],"contributors":[],"dates":[{"date":"2024-03-01","dateType":"Available"},{"date":"2024","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"GigaDB 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Yet the significant diversity within phage populations presents a considerable challenge. Currently, theres a notable lack of tools designed for large-scale characterization of phage receptor-binding proteins, which are crucial in determining the phage host range. \u003cbr\u003eIn this study, we present SpikeHunter, a deep learning method based on the ESM-2 protein language model. With SpikeHunter, we identified 231,965 diverse phage-encoded tailspike proteins, a crucial determinant of phage specificity that targets bacterial polysaccharide receptors, across 787,566 bacterial genomes from five virulent, antibiotic-resistant pathogens. Notably, 86.60% (143,200) of these proteins exhibited strong associations with specific bacterial polysaccharides. We discovered that phages with identical tailspike proteins can infect different bacterial species with similar polysaccharide receptors, underscoring the pivotal role of tailspike proteins in determining host range. The specificity is mainly attributed to the proteins C-terminal domain, which strictly correlates with host specificity during domain-swapping in tailspike proteins. Importantly, our dataset-driven predictions of phage-host specificity closely match the phage-host pairs observed in real-world phage therapy cases we studied. \u003cbr\u003eOur research provides a rich resource, including both the method and a database derived from a large-scale genomics survey. This substantially enhances understanding of phage specificity determinants at the strain level and offers a valuable framework for guiding phage selection in therapeutic applications.","lang":"en-US"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardNumber":"NSF2226183"},{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Library of Medicine"},{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Library of Medicine"},{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Library of Medicine"},{"funderIdentifierType":"Crossref Funder ID","funderName":"US National Library of 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As a result, teinturier varieties are of interest not only for their ability to enhance the pigmentation of wine blends but also for their health benefits. They also serve as valuable systems for investigating anthocyanin production in plants. Here, we assembled and annotated the Dakapo and Rubired genomes, two teinturier varieties. For Dakapo, we used a combination of Nanopore sequencing, Illumina sequencing, and scaffolding to the existing grapevine genome assembly to generate a final assembly of 508.5 Mbp. A combination approach of \u003ci\u003ede novo\u003c/i\u003e annotation and lifting over annotations from the existing grapevine reference genome resulted in the annotation of 36,940 genes in the Dakapo assembly. For Rubired, PacBio HiFi reads were assembled, scaffolded, and phased to generate a diploid assembly with two haplotypes 474.7-476.0 Mbp long. \u003ci\u003eDe novo\u003c/i\u003e annotation of the diploid Rubired genome yielded annotations for 56,681 genes across both haplotypes and unplaced contigs. The genomes for both varieties are highly contiguous (scaffold N50 \u0026gt; 24.9 Mbp) and highly complete (BUSCO \u0026gt; 97.7%). 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reports, surveys, and workshops, this NSF-funded GER Framework project engaged ~200 geoscience educators and researchers through a sequenced series of virtual and face-to-face events to share ideas, gain feedback, and create and revise priority research questions, or \"Grand Challenges\", that span 10 geoscience education research themes. For each theme, several Grand Challenges and recommended strategies have been proposed by the community. This framework development chapter describes the underlying project goal, its objectives, and its vision. It also outlines the processes used to develop the Framework and the intended scope and audience.","lang":"en"},{"descriptionType":"Other","description":"Citation: St. John, Kristen (2018). \"Framework Development\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/1.  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Fields of study encompassed in this domain include geomorphology, historical geology, mineralogy, petrology, stratigraphy, structural geology – all topics that are touched upon in introductory coursework, and constitute the core of an undergraduate geology curriculum. Combined with cognate coursework in biology, chemistry, physics, and mathematics, the conceptual load in the Solid Earth curriculum is significant. The risks of poor understanding of solid Earth concepts are non-trivial, ranging from the economic costs of commodities and energy to the potentially fatal impact of hazards from mass-wasting, flooding, volcanic activity, and earthquakes. As a result, undergraduate geoscience studies are faced with two main problems: (a) the determination of students' solid Earth misconceptions when they participate in geoscience coursework, including their persistence and the means to address them, and (b) the determination of optimal learning progressions in geoscience instruction to accommodate preparation of geoscience professionals and Earth science teachers, as well as general education students.  In this theme chapter, these two grand challenges are explored and recommended strategies are proposed to address them.","lang":"en"},{"descriptionType":"Other","description":"Citation: Pyle, Eric J.; Darling, Andy; Kreager, Zo; and Conrad, Susan Howes (2018). \"Research on Students' Conceptual Understanding of Geology/Solid Earth Science Content\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/2. DOI: 10.25885/ger_framework/2","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/2","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:10:57Z","registered":"2018-07-26T16:12:06Z","published":null,"updated":"2020-09-20T03:32:39Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/6","type":"dois","attributes":{"doi":"10.25885/ger_framework/6","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Texas A \u0026 M University"}],"givenName":"Eric M.","familyName":"Riggs","name":"Riggs, Eric M.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-8781-1452"}]},{"nameType":"Personal","affiliation":[{"name":"Grand Valley State University"}],"givenName":"Caitlin","familyName":"Callahan","name":"Callahan, Caitlin","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"American Meteorological Society"}],"givenName":"Jim","familyName":"Brey","name":"Brey, Jim","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Access and Success of Under-Represented Groups in the Geosciences"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Individualized instruction","subjectScheme":"LCSH"},{"subject":"Cultural pluralism","subjectScheme":"LCSH"},{"subject":"Minority college students--Recruiting","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"The geosciences as an allied group of fields touch virtually all aspects of the human enterprise: locating and providing water, energy and mineral resources; assuring a safe and resilient environment for civilization; and providing an understanding of how the Earth system functions today, in the past and into the future. Given how the geosciences touch the lives of all people, it should also be a field that is representative of all people, but this is not yet the case. Especially with the global importance of the geosciences growing and the geoscience workforce projected to encounter shortfalls of qualified practitioners in the coming decades, it is imperative that the geoscience education research community frame and investigate central questions that can help increase the diversity of the geosciences at all levels. We must find ways to attract all kinds of students, especially those from under-represented groups to our sciences and build programs, experiences and careers in which they thrive. The research challenges proposed in this chapter focus on two essential and interdependent perspectives (1) the point of view of the individual students, faculty and professionals as they manage their own internal balance of identities as they traverse curricula, programs and career pathways, and (2) a view that captures system-wide interactions around the individuals at all stages, including family, culture, department, university and society.","lang":"en"},{"descriptionType":"Other","description":"Citation: Riggs, Eric M.; Callahan, Caitlin; and Brey, Jim (2018). \"Research on Access and Success of Under-Represented Groups in the Geosciences\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/6. DOI: 10.25885/ger_framework/6","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/6","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:05:17Z","registered":"2018-07-26T16:06:30Z","published":null,"updated":"2020-09-20T03:32:38Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/5","type":"dois","attributes":{"doi":"10.25885/ger_framework/5","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"California State University-Chico"}],"givenName":"Rachel","familyName":"Teasdale","name":"Teasdale, Rachel","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0003-1820-8312"}]},{"nameType":"Personal","affiliation":[{"name":"Virginia Polytechnic Institute and State University"}],"givenName":"Hannah","familyName":"Scherer","name":"Scherer, Hannah","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Texas A \u0026 M University"}],"givenName":"Lauren","familyName":"Holder","name":"Holder, Lauren","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"CUNY Brooklyn College"}],"givenName":"Rebecca","familyName":"Boger","name":"Boger, Rebecca","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Nebraska at Lincoln"}],"givenName":"Cory","familyName":"Forbes","name":"Forbes, Cory","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Teaching about Earth in the Context of Societal Problems"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Social problems","subjectScheme":"LCSH"},{"subject":"Motivation in education","subjectScheme":"LCSH"},{"subject":"Undergraduates","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"Knowledge and consideration of societal issues are critical for students majoring in the geosciences, as well as for non-science students and the general public who vote and make decisions that should be based on sound science. Thus, the importance of integrating geoscience with other disciplines such as urban planning, social justice, politics, communications and more has become a critical call to action for geoscience researchers and educators that merits examination. Improving undergraduate STEM education with the use of relevant issues such as societal problems is a useful mechanism to help students find science to be personally relevant and to develop their interest based on societal contexts (e.g., as is currently being done in the InTeGrate program). The grand challenges in this chapter examine the use of societal issues to teach about the Earth, which include consideration of the impact on student learning, the design principles of curricula that best integrate geoscience content within the context of societal issues, and the assessment needed to measure the efficacy of these methods.","lang":"en"},{"descriptionType":"Other","description":"Citation: Teasdale, Rachel; Scherer, Hannah; Holder, Lauren; Boger, Rebecca; and Forbes, Cory (2018). \"Research on Teaching about Earth in the Context of Societal Problems\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/5. DOI: 10.25885/ger_framework/5","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/5","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:04:08Z","registered":"2018-07-26T16:05:29Z","published":null,"updated":"2020-09-20T03:32:38Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/7","type":"dois","attributes":{"doi":"10.25885/ger_framework/7","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"University of South Carolina"}],"givenName":"Katherine","familyName":"Ryker","name":"Ryker, Katherine","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0002-3781-3422"}]},{"nameType":"Personal","affiliation":[{"name":"Temple University"}],"givenName":"Allison J.","familyName":"Jaeger","name":"Jaeger, Allison J.","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Cognitive Domain in Geoscience Learning:"},{"titleType":"Subtitle","lang":"en","title":"Temporal and Spatial Reasoning"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Reasoning (Psychology)","subjectScheme":"LCSH"},{"subject":"Competency-based education","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"nameType":"Personal","affiliation":[{"name":"University of Alabama at Birmingham"}],"givenName":"Scott","familyName":"Brande","name":"Brande, Scott","contributorType":"Researcher","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Texas at El Paso"}],"givenName":"Mariana","familyName":"Guereque","name":"Guereque, Mariana","contributorType":"Researcher","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Michigan State University"}],"givenName":"Julie","familyName":"Libarkin","name":"Libarkin, Julie","contributorType":"Researcher","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Temple University"}],"givenName":"Thomas F.","familyName":"Shipley","name":"Shipley, Thomas F.","contributorType":"Researcher","nameIdentifiers":[]},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"The geosciences are characterized by their particular application of and reliance on temporal and spatial reasoning. Geoscientists must be able to apply their knowledge across a variety of scales. The ability to engage with this kind of task represents a great shift in thinking from where most students begin their studies, be that in K-12 or college. In order to understand how people's ability to spatial and temporal reasoning changes over time requires identification of what skills are essential, assessment of those skills, and then exploration of the impacts of different targeted interventions in geoscience contexts. While more is known about how people reason spatially as compared with temporally, there are still significant gaps in our understanding of spatial reasoning in the geosciences. There are opportunities to build on lessons learned from previous investigations of spatial thinking (e.g. the Spatial Intelligence and Learning Center), including how a community can investigate a specific line of reasoning. There is also a need to build on established research from other domains, from anthropology to cognitive science to physics. In this chapter the authors identified and describe three grand challenges to better understand the need for and growth of spatial and temporal reasoning in geoscience education. These include identifying what reasonings or skills are essential to the geosciences (both broadly and within subdisciplines), and the intertwined challenge of how to assess those reasonings and use those results to improve on what students are learning from their geoscience experiences.","lang":"en"},{"descriptionType":"Other","description":"Citation: Ryker, Katherine; Jaeger, Allison J.; Brande, Scott; Guereque, Mariana; Libarkin, Julie; and Shipley, Thomas F. (2018). \"Research on Cognitive Domain in Geoscience Learning: Temporal and Spatial Reasoning\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/7. DOI: 10.25885/ger_framework/7","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/7","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:09:56Z","registered":"2018-07-26T16:11:05Z","published":null,"updated":"2020-09-20T03:32:38Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/9","type":"dois","attributes":{"doi":"10.25885/ger_framework/9","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Arizona State University-Tempe"}],"givenName":"Steven","familyName":"Semken","name":"Semken, Steven","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0002-4607-1256"}]},{"nameType":"Personal","affiliation":[{"name":"University of Wisconsin-Whitewater"}],"givenName":"Juk","familyName":"Bhattacharyya","name":"Bhattacharyya, Juk","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Paleontological Research Institution"}],"givenName":"Don","familyName":"Duggan-Haas","name":"Duggan-Haas, Don","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"The Concord Consortium"}],"givenName":"Amy","familyName":"Pallant","name":"Pallant, Amy","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"North Carolina State University"}],"givenName":"Jennifer","familyName":"Wiggen","name":"Wiggen, Jennifer","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Instructional Strategies to Improve Geoscience Learning in Different Settings and with Different Technologies"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Educational technology","subjectScheme":"LCSH"},{"subject":"Effective teaching","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"Geoscience instruction today is carried out in a range of settings and with variously situated and richly contextualized teaching modalities. However, the pace and the excitement of technological and methodological advances in education tend to outstrip the more deliberate progress of relevant educational research and assessment. Further, geoscience education receives less attention and support on a national scale than do biology, chemistry, and physics education. As a result, many recent influential studies which demonstrated the effectiveness of active learning in undergraduate STEM, include little or no data from geoscience education. In order to close these gaps and render future instructional strategies as effective as possible, (a) there must be better coordination among researchers and educators in our own professional community and with those in other STEM disciplines; (b) higher standards of evidence must be applied to research in many cases; and (c) certain barriers at the instructional level to full and effective implementation of best practices must still be overcome. In this theme chapter, five grand challenges related to these issues are identified and described to spur more effective, accessible, inclusive, relevant, and practical geoscience teaching and learning.","lang":"en"},{"descriptionType":"Other","description":"Citation: Semken, Steven; Bhattacharyya, Juk; Duggan-Haas, Don; and Pallant, Amy (2018). \"Research on Instructional Strategies to Improve Geoscience Learning in Different Settings and with Different Technologies\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/9. DOI: 10.25885/ger_framework/9","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/9","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:01:53Z","registered":"2018-07-26T16:02:54Z","published":null,"updated":"2020-09-20T03:32:37Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/8","type":"dois","attributes":{"doi":"10.25885/ger_framework/8","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Lamont-Doherty Earth Observatory"}],"givenName":"Kim A.","familyName":"Kastens","name":"Kastens, Kim A.","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Nebraska at Omaha"}],"givenName":"Ashlee","familyName":"Dere","name":"Dere, Ashlee","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Texas at El Paso"}],"givenName":"Deana","familyName":"Pennington","name":"Pennington, Deana","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of South Florida"}],"givenName":"Vic","familyName":"Ricchezza","name":"Ricchezza, Vic","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Cognitive Domain in Geoscience Learning:"},{"titleType":"Subtitle","lang":"en","title":"Quantitative Reasoning, Problem Solving, and Use of Models"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Quantitative research","subjectScheme":"LCSH"},{"subject":"Model-based reasoning","subjectScheme":"LCSH"},{"subject":"Mathematical models","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"Models (from simple mental models to complex computational models) are used by geoscientists to conceptualize and better understand the Earth system and to make predictions. Earth processes affect the human condition and result in hazards and complex issues that require both expert and citizenry decision-making about mitigation and adaptation. In addition, a wide range of Earth materials (e.g., mineral, rock, water) are valued resources that need sustainable management. All of these challenges require recognition of the problem (problem-finding), and the development and application of problem-solving skills. In addition, Earth system understanding and problem-solving benefit strongly from quantitative reasoning. Quantitative reasoning, problem-solving, and use of models present many daunting challenges to both students and instructors. All are valued by the professional geoscience community and by employers, and all would benefit from more education research. In this chapter, grand challenges and recommended strategies for each of these areas are identified and described.","lang":"en"},{"descriptionType":"Other","description":"Kastens, Kim A.; Dere, Ashlee; Pennington, Deana; and Ricchezza, Vic (2018). \"Research on Cognitive Domain in Geoscience Learning: Quantitative Reasoning, Problem Solving, and Use of Models\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/8. DOI: 10.25885/ger_framework/8","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/8","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:02:58Z","registered":"2018-07-26T16:04:27Z","published":null,"updated":"2020-09-20T03:32:37Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/10","type":"dois","attributes":{"doi":"10.25885/ger_framework/10","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Auburn University"}],"givenName":"Karen S.","familyName":"McNeal","name":"McNeal, Karen S.","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Whatcom Community College"}],"givenName":"Kaatje","familyName":"Van der Hoeven Kraft","name":"Van der Hoeven Kraft, Kaatje","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Pasadena City College"}],"givenName":"Elizabeth","familyName":"Nagy-Shadman","name":"Nagy-Shadman, Elizabeth","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Valencia College"}],"givenName":"Mary","familyName":"Beck","name":"Beck, Mary","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"North Carolina University"}],"givenName":"Jason","familyName":"Jones","name":"Jones, Jason","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Geoscience Students' Self-Regulated Learning, Metacognition, and Affect"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Educational psychology","subjectScheme":"LCSH"},{"subject":"Metacognition","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"It is how individuals navigate content through their affect, their ability to self-regulate, and their metacognitive capabilities that ultimately determines whether and how they interact with the content. Many of the questions researchers in the fields of education psychology, cognitive science, and science education still have about these matters are in direct alignment with the interests of geoscience education research (GER). Some of these emergent lines of inquiry in these other fields can inform GER through the use of more-established theories and methodologies. The geosciences may be a unique context in which these questions can be investigated and the findings generated from GER researchers may be of interest to the broader learning science audience which, in turn, may provide geoscience education researchers new dissemination outlets and interested audiences to publish and communicate their research findings. In this theme chapter, the authors articulate four grand challenges that highlight needed areas of research on self-regulated learning, metacognition and affect. These are organized around important ways in which these factors emerge in teaching and learning: in the development of student skills, in the support of a diverse population of learners, in the support of educators teaching these students, and in assuring that research on these factors is of the highest standards.","lang":"en"},{"descriptionType":"Other","description":"Citation:  McNeal, Karen S.; Van der Hoeven Kraft, Kaatje; Nagy-Shadman, Elizabeth; and Beck, Mary (2018). \"Research on Geoscience Students' Self-Regulated Learning, Metacognition, and Affect\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/10. DOI: 10.25885/ger_framework/10","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/10","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T16:00:35Z","registered":"2018-07-26T16:01:52Z","published":null,"updated":"2020-09-20T03:32:36Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/3","type":"dois","attributes":{"doi":"10.25885/ger_framework/3","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Iowa State University"}],"givenName":"Cinzia","familyName":"Cervato","name":"Cervato, Cinzia","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"UNAVCO"}],"givenName":"Donna","familyName":"Charlevoix","name":"Charlevoix, Donna","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of Colorado at Boulder"}],"givenName":"Anne","familyName":"Gold","name":"Gold, Anne","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Lake Superior State University"}],"givenName":"Hari","familyName":"Kandel","name":"Kandel, Hari","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Students' Conceptual Understanding of Environmental, Ocean, Atmosphere, and Climate Science Content"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Climatology","subjectScheme":"LCSH"},{"subject":"Oceanography","subjectScheme":"LCSH"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Earth and related environmental sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Atmosphere--Research","subjectScheme":"LCSH"},{"subject":"Ecology","subjectScheme":"LCSH"},{"schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"At the interface between atmosphere, hydrosphere, and biosphere, this theme chapter covers content that is societally crucial but publicly controversial and fraught by misconceptions and misinformation. Climate science is an interdisciplinary field that straddles the natural and social sciences; understanding its processes requires system-thinking, understanding mathematical models, and appreciation of its human and societal components. Recent data show that extreme weather and climate events have become more frequent in the past decades. These include extreme temperatures, floods, like the ones associated with the series of very powerful hurricanes that made an unprecedented number of landfalls in August and September 2017 and unusual drought conditions and forest fires across the Western US in the summer of 2017. Studies like these emphasize the complexity of climate science and highlight the importance of climate change adaptation. However, there is a significant disparity in the distribution of vulnerability and readiness to impacts of climate change around the world. In this theme chapter, authors have identified five grand challenges to the conceptual understanding of environmental, oceanic, atmospheric and climate science, and proposed strategies for the geoscience education research community.","lang":"en"},{"descriptionType":"Other","description":"Citation:  Cervato, Cinzia; Charlevoix, Donna; Gold, Anne; and Kandel, Hari(2018). \"Research on Students' Conceptual Understanding of Environmental, Oceanic, Atmospheric, and Climate Science Content\". In St. John, K (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/3. DOI: 10.25885/ger_framework/3"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/3","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":1,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T15:59:39Z","registered":"2018-07-26T16:00:50Z","published":null,"updated":"2020-09-20T03:32:36Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/15","type":"dois","attributes":{"doi":"10.25885/ger_framework/15","identifiers":[],"creators":[{"nameType":"Organizational","affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"A Community Framework for Geoscience Education Research"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"Collection","resourceTypeGeneral":"Collection","citeproc":"report","bibtex":"misc","ris":"GEN","resourceType":"Report"},"relatedIdentifiers":[{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/1","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/2","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/3","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/4","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/5","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/6","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/7","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/8","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/9","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/10","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/11","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/12","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/13","relatedIdentifierType":"DOI"},{"relationType":"HasPart","relatedIdentifier":"10.25885/ger_framework/14","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"In order to guide future investments of time and resources in geoscience education research (GER), the community has developed a framework of grand challenges across ten major themes in GER. These grand challenges can provide direction to current and future researchers about where the community thinks effort should be made to answer some fundamental questions about undergraduate geoscience teaching and learning. This Community Framework for GER is comprised of ten theme chapters, as well as chapters on the development of the framework project, a synthesis of the findings and potential synergies, and on communication strategies for the transformation of geoscience teaching practice.","lang":"en"},{"descriptionType":"TableOfContents","description":"Framework Development, by Kristen St. John, James Madison University\n            \n            Research on Students' Conceptual Understanding of Geology/Solid Earth Science Content, by Eric Pyle, James Madison University; Andy Darling, Colorado State University; Zo Kreager, Northern Illinois University; and Susan Howes Conrad, Dutchess Community College\n            \n            Research on Students' Conceptual Understanding of Environmental, Ocean, Atmosphere, and Climate Science Content, by Cinzia Cervato, Iowa State University; Donna Charlevoix, UNAVCO; Anne Gold, University of Colorado at Boulder; and Hari Kandel, Lake Superior State University\n            \n            Research on Elementary, Middle, and Secondary Earth and Space Sciences Teacher Education, by Heather Petcovic, Western Michigan University; Jason Cervenec, The Ohio State University; Kim Cheek, University of North Florida; Robyn Dahl, Western Washington University; and Nancy Price, Portland State University, with editorial contributions from Eric Pyle, James Madison University\n            \n            Research on Teaching about Earth in the Context of Societal Problems, by Rachel Teasdale, California State University-Chico; Hannah Scherer, Virginia Polytechnic Institute and State Univ; Lauren Holder, Texas A \u0026amp; M University; Rebecca Boger, CUNY Brooklyn College; Cory Forbes, University of Nebraska at Lincoln\n            \n            Research on Access and Success of Under-Represented Groups in the Geosciences, by Eric Riggs, Texas A \u0026amp; M University; Caitlin Callahan, Grand Valley State University; and Jim Brey, American Meteorological Society\n            \n            Research on Cognitive Domain in Geoscience Learning: Temporal and Spatial Reasoning, by Katherine Ryker, University of South Carolina and Allison J. Jaeger, Temple University. With contributions from: Scott Brande, University of Alabama at Birmingham; Mariana Guereque, The University of Texas at El Paso; Julie Libarkin, Michigan State University; and Thomas F. Shipley, Temple University\n            \n            Research on Cognitive Domain in Geoscience Learning: Quantitative Reasoning, Problem Solving, and Use of Models, by Kim Kastens, Lamont-Doherty Earth Observatory; Ashlee Dere, University of Nebraska at Omaha; Deana Pennington, The University of Texas at El Paso; and Vic Ricchezza, University of South Florida\n            \n            Research on Instructional Strategies to Improve Geoscience Learning in Different Settings and with Different Technologies, by Steven Semken, Arizona State University at Tempe; Juk Bhattacharyya, University of Wisconsin-Whitewater; Don Duggan-Haas, Paleontological Research Institution; Amy Pallant, The Concord Consortium; and Jennifer Wiggen, North Carolina State University\n            \n            Research on Geoscience Students' Self-Regulated Learning, Metacognition, and Affect, by Karen S. McNeal, Auburn University; Kaatje Van der Hoeven Kraft, Whatcom Community College; Elizabeth Nagy-Shadman, Pasadena City College; Mary Beck, Valencia College, and Jason Jones, North Carolina University\n            \n            Research on Institutional Change and Professional Development, by Kelsey Bitting, Northeastern University; Leilani Arthurs, University of Colorado at Boulder; LeeAnna Chapman, University of San Diego; Heather Macdonald, College of William and Mary; and Cathy Manduca, SERC-Carleton College\n            \n            Synthesis: Discussion and Implications, by Kristen St. John, James Madison University; Kelsey Bitting, Northeastern University; Cinzia Cervato, Iowa State University; Kim A. Kastens, Lamont-Doherty Earth Observatory; Heather Macdonald, College of William \u0026amp; Mary; John R. McDaris, SERC at Carleton College; Karen S. McNeal, Auburn University; Heather L. Petcovic, Western Michigan University; Eric J. Pyle, James Madison University; Eric M. Riggs, Texas A\u0026amp;M University; Katherine Ryker, University of South Carolina; Steven Semken, Arizona State University-Tempe; Rachel Teasdale, California State University-Chico\n            \n            Closing the Loop: Communication for Transformation of Geoscience Teaching Practice, by Eric J. Pyle, James Madison University; Steven Semken, Arizona State University-Tempe; Andy Darling, Colorado State University","lang":"en"},{"descriptionType":"Other","description":"Citation: St. John, K. (Ed.) (2018). A Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from http://commons.lib.jmu.edu/ger_framework/15. DOI: 10.25885/ger_framework/15","lang":"en"}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"Crossref Funder ID","funderName":"National Science Foundation","funderIdentifier":"https://doi.org/10.13039/501100008982","awardTitle":"A Framework for Transformative Geoscience Education Research","awardNumber":"DUE-1708228","awardUri":"https://nsf.gov/awardsearch/showAward?AWD_ID=1708228"}],"url":"http://commons.lib.jmu.edu/ger_framework/15","contentUrl":null,"metadataVersion":1,"schemaVersion":null,"source":"legacy","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":14,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2018-07-26T15:57:53Z","registered":"2018-07-26T15:59:20Z","published":null,"updated":"2020-09-20T03:32:35Z"},"relationships":{"client":{"data":{"id":"jmu.viva","type":"clients"}}}},{"id":"10.25885/ger_framework/4","type":"dois","attributes":{"doi":"10.25885/ger_framework/4","identifiers":[],"creators":[{"nameType":"Personal","affiliation":[{"name":"Western Michigan University"}],"givenName":"Heather L.","familyName":"Petcovic","name":"Petcovic, Heather L.","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0002-1669-6802"}]},{"nameType":"Personal","affiliation":[{"name":"Ohio State University"}],"givenName":"Jason","familyName":"Cervenec","name":"Cervenec, Jason","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"University of North Florida"}],"givenName":"Kim","familyName":"Cheek","name":"Cheek, Kim","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Western Washington University"}],"givenName":"Robyn","familyName":"Dahl","name":"Dahl, Robyn","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[{"name":"Portland State University"}],"givenName":"Nancy","familyName":"Price","name":"Price, Nancy","nameIdentifiers":[]}],"titles":[{"lang":"en","title":"Research on Elementary, Middle, and Secondary Earth and Space Sciences Teacher Education"}],"publisher":{"name":"JMU Scholarly Commons"},"container":{"identifier":"10.25885/ger_framework/15","identifierType":"DOI","type":"Series"},"publicationYear":2018,"subjects":[{"subject":"Earth sciences--Study and teaching","subjectScheme":"LCSH"},{"subject":"Education, Elementary","subjectScheme":"LCSH"},{"subject":"Education, Secondary","subjectScheme":"LCSH"},{"subject":"Teachers--Training of","subjectScheme":"LCSH"}],"contributors":[{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Kristen","familyName":"St. John, Kristen","name":"St. John, Kristen, Kristen","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"https://orcid.org/0000-0001-7045-7485"}],"contributorType":"Editor"},{"nameType":"Personal","affiliation":[{"name":"James Madison University"}],"givenName":"Eric","familyName":"Pyle","name":"Pyle, Eric","contributorType":"Editor","nameIdentifiers":[]},{"affiliation":[],"name":"JMU Scholarly Commons","nameIdentifiers":[]},{"nameType":"Personal","affiliation":[],"givenName":"Science Education Resource Center","familyName":"Carleton College","name":"Carleton College, Science Education Resource Center","nameIdentifiers":[{"nameIdentifierScheme":"LCNAF","nameIdentifier":"no2010146960"}],"contributorType":"Sponsor"},{"affiliation":[],"name":"National Association Of Geoscience Teachers","nameIdentifiers":[]}],"dates":[{"date":"2018","dateType":"Created"},{"date":"2018","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"Text","citeproc":"article-journal","bibtex":"article","ris":"RPRT","resourceType":"Chapter"},"relatedIdentifiers":[{"relationType":"IsPartOf","relatedIdentifier":"10.25885/ger_framework/15","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["application/pdf"],"version":null,"rightsList":[{"rightsUri":"https://creativecommons.org/licenses/by-nc/4.0","rights":"CreativeCommons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)"}],"descriptions":[{"descriptionType":"Abstract","description":"In order to fully engage with the vision of the Framework for K-12 Science Education and the NGSS, our nation needs a diverse and well prepared K-12 science teacher workforce. And in order for ESS to gain equal status with other sciences, the geoscience community must ensure that the K-12 science teacher workforce is adequately prepared to teach ESS core knowledge and practices. This is a challenging endeavor and complicated by the fact that the K-12 teacher education landscape is highly variable across institutions in terms of how much ESS content is included, how programs are structured, and how ESS fits into the larger institutional context. Teacher education exists in a complex landscape that involve many domains of research. This theme chapter focuses on teacher education research that most directly aligns to the undergraduate teaching and learning experience. Three grand challenges emerged from discussion and reflections on the existing literature and are poised to guide future research on undergraduate K-12 teacher education.","lang":"en"},{"descriptionType":"Other","description":"Citation: Petcovic, Heather L.; Cervenec, Jason; Cheek, Kim; Dahl, Robyn; and Price, Nancy (2018). \"Research on Elementary, Middle, and Secondary Earth and Space Sciences Teacher Education\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/4. 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To achieve these goals, substantial improvements in areas as broad as instruction, mentoring and advising, and departmental climate must be made. Our ability to change can be supported by a better understanding of how educators, departments, and institutions change and how professional development opportunities foster and support productive change. This theme chapter considers how future geoscience education research can address issues of change in institutions of higher education and professional development that will promote high-quality geoscience education. Specifically, it identifies and describes three grand challenges that connect to the following components: the individual geoscience instructor, the departments and programs in which geoscience instructors teach, and the broader communities in which these departments operate.","lang":"en"},{"descriptionType":"Other","description":"Citation: Bitting, Kelsey; Arthurs, Leilani; Chapman, LeeAnna; and Macdonald, Heather(2018). \"Research on Institutional Change and Professional Development\". In St. John, K. (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/11. 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important goal: to improve undergraduate teaching and learning about the Earth by focusing the power of Geoscience Education Research (GER) on a set of ambitious, high-priority, community-endorsed grand challenges. Working groups, through examination of the literature and with the aid of reviewers' insights, identified two to five grand challenges for each of the ten research themes. The thematic grand challenges illuminate interconnected paths for future GER. Collective this creates a guiding framework to harness the power of GER to improve undergraduate teaching and learning about the Earth. While the individual theme chapters lay out the rationales for those large-scale \"grand challenge\" research questions and offer strategies for addressing them, here the purpose is to summarize and synthesize - to highlight thematic research priorities and synergies that may be avenues for research efficiencies and powerful outcomes.","lang":"en"},{"descriptionType":"Other","description":"Citation: St. John, Kristen; Bitting, Kelsey; Cervato, Cinzia; Kastens, Kim A.; Macdonald, Heather; McDaris, John R.; McNeal, Karen S.; Petcovic, Heather L.; Pyle, Eric J.; Riggs, Eric M.; Ryker, Katherine; Semken, Steven; and Teasdale, Rachel (2018)., \"Synthesis: Discussion and Implications\". In St. John, K (Ed.) (2018). Community Framework for Geoscience Education Research. National Association of Geoscience Teachers. Retrieved from\n            http://commons.lib.jmu.edu/ger_framework/12. 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