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

Jun Ding | Zendy; Xiaoman Li | Zendy; Haiyan Hu | Zendy

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

Author(s) -

Jun Ding,

Xiaoman Li,

Haiyan Hu

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx606

Subject(s) - identification (biology) , computer science , competition (biology) , microrna , recall , precision and recall , computational biology , machine learning , data mining , artificial intelligence , biology , gene , genetics , ecology , psychology , cognitive psychology

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.

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