miMsg: a target enrichment algorithm for predicted miR–mRNA interactions based on relative ranking of matched expression data | Zendy

Martin A. Rijlaarsdam | Zendy; David Rijlaarsdam | Zendy; Ad Gillis | Zendy; Lambert C. J. Dorssers | Zendy; Leendert H. J. Looijenga | Zendy

Open Access

miMsg: a target enrichment algorithm for predicted miR–mRNA interactions based on relative ranking of matched expression data

Author(s) -

Martin A. Rijlaarsdam,

David Rijlaarsdam,

Ad Gillis,

Lambert C. J. Dorssers,

Leendert H. J. Looijenga

Publication year - 2013

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/btt246

Subject(s) - ranking (information retrieval) , context (archaeology) , computer science , algorithm , messenger rna , set (abstract data type) , source code , data mining , function (biology) , matlab , computational biology , bioinformatics , machine learning , biology , gene , genetics , programming language , paleontology , operating system

Algorithms predicting microRNA (miR)-mRNA interactions generate high numbers of possible interactions, many of which might be non-existent or irrelevant in a certain biological context. It is desirable to develop a transparent, user-friendly, unbiased tool to enrich miR-mRNA predictions.

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