Data from: Determining the minimum number of protein-protein interactions required to support known protein complexes - Nakajima, Natsu; Hayashida, Morihiro; Jansson, Jesper; Maruyama, Osamu; Akutsu, Tatsuya (Dryad, 2018)
The prediction of protein complexes from protein-protein interactions
(PPIs) is a well-studied problem in bioinformatics. However, the currently
available PPI data is not enough to describe all known protein complexes.
In this paper, we express the problem of determining the minimum number of
(additional) required protein-protein interactions as a graph theoretic
problem under the constraint that each complex constitutes a connected
component in a PPI network. For this problem, we develop two computational
methods: one is based on integer linear programming (ILPMinPPI) and the
other one is based on an existing greedy-type approximation algorithm
(GreedyMinPPI) originally developed in the context of communication and
social networks. Since the former method is only applicable to datasets of
small size, we apply the latter method to a combination of the CYC2008
protein complex dataset and each of eight PPI datasets (STRING, MINT,
BioGRID, IntAct, DIP, BIND, WI-PHI, iRefIndex). The results show that the
minimum number of additional required PPIs ranges from 51 (STRING) to 964
(BIND), and that even the four best PPI databases, STRING (51), BioGRID
(67), WI-PHI (93) and iRefIndex (85), do not include enough PPIs to form
all CYC2008 protein complexes. We also demonstrate that the proposed
problem framework and our solutions can enhance the prediction accuracy of
existing PPI prediction methods. ILPMinPPI can be freely downloaded from
http://sunflower.kuicr.kyoto-u.ac.jp/~nakajima/.
ILPMinPPI_data
Keywords: Protein interaction networks; Algorithms; Database and informatics methods; Linear programming; Protein interactions; Forecasting; Protein-protein interactions; Protein complexes