MicroTar: predicting microRNA targets from RNA duplexes.
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.
Thadani
Rahul
R
Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore 117543. rahul.thadani@nus.edu.sg
Tammi
Martti T
MT
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
D035683:MicroRNAs; D009692:Nucleic Acid Heteroduplexes; D012333:RNA, Messenger