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

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 detec...

• Type: Conference
• Year: 2006
• Where: RECOMB
• Authors: Jim C. Huang, Quaid Morris, Brendan J. Frey
• Keywords: Candidate MiRNA Targets, Computational Biology, Gene Expression, MiRNA Targets, RECOMB 2006