Ccmir: A Computational Approach For Competitive And Cooperative Microrna Binding Prediction
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.
Publication Date
1-15-2018
Publication Title
Bioinformatics
Volume
34
Issue
2
Number of Pages
198-206
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1093/bioinformatics/btx606
Copyright Status
Unknown
Socpus ID
85040627090 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85040627090
STARS Citation
Ding, Jun; Li, Xiaoman; and Hu, Haiyan, "Ccmir: A Computational Approach For Competitive And Cooperative Microrna Binding Prediction" (2018). Scopus Export 2015-2019. 9096.
https://stars.library.ucf.edu/scopus2015/9096