alexa Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Betel D, Koppal A, Agius P, Sander C, Leslie C

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Abstract mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
This article was published in Genome Biol and referenced in Journal of Data Mining in Genomics & Proteomics

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