CCmiR: a computational approach for competitive and cooperative microRNA binding prediction

Bioinformatics. 2018 Jan 15;34(2):198-206. doi: 10.1093/bioinformatics/btx606.

Abstract

Motivation: The identification of microRNA (miRNA) target sites is important. In the past decade, dozens of computational methods have been developed to predict miRNA target sites. Despite their existence, rarely does a method consider the well-known competition and cooperation among miRNAs when attempts to discover target sites. To fill this gap, we developed a new approach called CCmiR, which takes the cooperation and competition of multiple miRNAs into account in a statistical model to predict their target sites.

Results: Tested on four different datasets, CCmiR predicted miRNA target sites with a high recall and a reasonable precision, and identified known and new cooperative and competitive miRNAs supported by literature. Compared with three state-of-the-art computational methods, CCmiR had a higher recall and a higher precision.

Availability and implementation: CCmiR is freely available at http://hulab.ucf.edu/research/projects/miRNA/CCmiR.

Supplementary information: Supplementary data are available at Bioinformatics online.