Detecting MicroRNA Targets by Linking Sequence, MicroRNA and Gene Expression Data

  • Jim C. Huang
  • Quaid D. Morris
  • Brendan J. Frey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3909)


MicroRNAs (miRNAs) have recently been discovered as an important class of non-coding RNA genes that play a major role in regulating gene expression, providing a means to control the relative amounts of mRNA transcripts and their protein products. Although much work has been done in the genome-wide computational prediction of miRNA genes and their target mRNAs, two open questions are how miRNAs regulate gene expression and how to efficiently detect bona fide miRNA targets from a large number of candidate miRNA targets predicted by existing computational algorithms. In this paper, we present evidence that miRNAs function by post-transcriptional degradation of mRNA target transcripts: based on this, we propose a novel probabilistic model that accounts for gene expression using miRNA expression data and a set of candidate miRNA targets. A set of underlying miRNA targets are learned from the data using our algorithm, GenMiR (Generative model for miRNA regulation). Our model scores and detects 601 out of 1,770 targets obtained from TargetScanS in mouse at a false detection rate of 5%. Our high-confidence miRNA targets include several which have been previously validated by experiment: the remainder potentially represent a dramatic increase in the number of known miRNA targets.


mRNA Transcript miRNA Target Candidate Target miRNA Regulation MicroRNA Target 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jim C. Huang
    • 1
  • Quaid D. Morris
    • 2
  • Brendan J. Frey
    • 1
    • 2
  1. 1.Probabilistic and Statistical Inference GroupUniversity of TorontoTorontoCanada
  2. 2.Banting and Best Department of Medical ResearchUniversity of TorontoTorontoCanada

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