title: MicroTar: predicting microRNA targets from RNA duplexes.
abstract: BACKGROUND
  The accurate prediction of a comprehensive set of messenger RNAs (targets) regulated by animal microRNAs (miRNAs) remains an open problem. In particular, the prediction of targets that do not possess evolutionarily conserved complementarity to their miRNA regulators is not adequately addressed by current tools.
  
  
  RESULTS
  We have developed MicroTar, an animal miRNA target prediction tool based on miRNA-target complementarity and thermodynamic data. The algorithm uses predicted free energies of unbound mRNA and putative mRNA-miRNA heterodimers, implicitly addressing the accessibility of the mRNA 3' untranslated region. MicroTar does not rely on evolutionary conservation to discern functional targets, and is able to predict both conserved and non-conserved targets. MicroTar source code and predictions are accessible at http://tiger.dbs.nus.edu.sg/microtar/, where both serial and parallel versions of the program can be downloaded under an open-source licence.
  
  
  CONCLUSIONS
  MicroTar achieves better sensitivity than previously reported predictions when tested on three distinct datasets of experimentally-verified miRNA-target interactions in C. elegans, Drosophila, and mouse.
authors.affiliation: Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543. rahul.thadani@nus.edu.sg
authors.forename: Rahul
authors.initials: R
authors.lastname: Thadani
authors.forename: Martti T
authors.initials: MT
authors.lastname: Tammi
mesh_terms: D000465:Algorithms; D000818:Animals; D017173:Caenorhabditis elegans; D004331:Drosophila melanogaster; D051379:Mice; D035683:MicroRNAs / Q000737:chemistry*; D009690:Nucleic Acid Conformation; D009692:Nucleic Acid Heteroduplexes / Q000737:chemistry*; D012333:RNA, Messenger / Q000737:chemistry*; D012984:Software
chemical_list: D035683:MicroRNAs; D009692:Nucleic Acid Heteroduplexes; D012333:RNA, Messenger