[HTML][HTML] Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

D Betel, A Koppal, P Agius, C Sander, C Leslie - Genome biology, 2010 - Springer
Genome biology, 2010Springer
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 …
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.
Springer