Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Academic Article uri icon

Overview

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.

publication date

  • August 27, 2010

Research

keywords

  • Artificial Intelligence
  • MicroRNAs

Identity

PubMed Central ID

  • PMC2945792

Scopus Document Identifier

  • 77955963884

Digital Object Identifier (DOI)

  • 10.1186/gb-2010-11-8-r90

PubMed ID

  • 20799968

Additional Document Info

volume

  • 11

issue

  • 8