mirMark: a site-level and UTR-level classifier for miRNA target prediction.

Abstract:

:MiRNAs play important roles in many diseases including cancers. However computational prediction of miRNA target genes is challenging and the accuracies of existing methods remain poor. We report mirMark, a new machine learning-based method of miRNA target prediction at the site and UTR levels. This method uses experimentally verified miRNA targets from miRecords and mirTarBase as training sets and considers over 700 features. By combining Correlation-based Feature Selection with a variety of statistical or machine learning methods for the site- and UTR-level classifiers, mirMark significantly improves the overall predictive performance compared to existing publicly available methods. MirMark is available from https://github.com/lanagarmire/MirMark.

journal_name

Genome Biol

journal_title

Genome biology

authors

Menor M,Ching T,Zhu X,Garmire D,Garmire LX

doi

10.1186/s13059-014-0500-5

subject

Has Abstract

pub_date

2014-01-01 00:00:00

pages

500

issue

10

eissn

1474-7596

issn

1474-760X

pii

s13059-014-0500-5

journal_volume

15

pub_type

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