10.6084/M9.FIGSHARE.701215
Ignacio Sanchez Caballero
Improving microRNA target prediction by performance-based algorithm combination
<p>MicroRNAs have been at the center stage of the biomedical community for more than a decade now, after a team of scientists working at Harvard University in Cam- bridge discovered their vital role in the regulation of gene expression [1]. Since then, the use of bioinformatic tools has become a major accelerator in our understanding of microRNA function. Many algorithms have been created to predict where mi- croRNAs are encoded, as well as what genes they regulate [2–10]. Unfortunately, due to the popularity of the field, it is not always clear which of the available computa- tional methods is best suited for determining which mRNA transcripts are regulated by which microRNAs.</p>
<p>We propose a straightforward method to combine the tens of currently available prediction algorithms, and assign them a credibility measure based on their previous performance to simplify the task of experimental validation.</p>
60102 Bioinformatics
figshare
2013
2013-05-10
2013-05-10
Journal contribution
1442315 Bytes
CC BY 4.0