Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites Journal Article


Authors: Betel, D.; Koppal, A.; Agius, P.; Sander, C.; Leslie, C.
Article Title: Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites
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.
Keywords: recognition; posttranscriptional regulation; transcripts; messenger-rnas; elements; rna-binding protein; c.; elegans; complementary; accessibility; determinants
Journal Title: Genome Biology
Volume: 11
Issue: 8
ISSN: 1465-6906
Publisher: Biomed Central Ltd  
Date Published: 2010-01-01
Start Page: epub
Language: English
ACCESSION: ISI:000283777600011
DOI: 10.1186/gb-2010-11-8-r90
PROVIDER: wos
PMCID: PMC2945792
PUBMED: 20799968
Notes: --- - Article - R90 - "Source: Wos"
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  1. Anjali Jagannatha Koppal
    1 Koppal
  2. Doron Betel
    10 Betel
  3. Chris Sander
    210 Sander
  4. Christina Leslie
    188 Leslie
  5. Phaedra Agius
    11 Agius