BMC Genomics: A Bayesian approach for identifying miRNA targets by combining sequence prediction and gene expression profiling

Hui LiuDong YueLin ZhangYidong ChenShou-Jiang Gao & Yufei Huang

Abstract

Background

MicroRNAs (miRNAs) are single-stranded non-coding RNAs shown to plays important regulatory roles in a wide range of biological processes and diseases. The functions and regulatory mechanisms of most miRNAs are still poorly understood in part because of the difficulty in identifying the miRNA regulatory targets. To this end, computational methods have evolved as important tools for genome-wide target screening. Although considerable work in the past few years has produced many target prediction algorithms, most of them are solely based on sequence, and the accuracy is still poor. In contrast, gene expression profiling from miRNA transfection experiments can provide additional information about miRNA targets. However, most of the existing research assumes down-regulated mRNAs as targets. Given the fact that the primary function of miRNA is protein inhibition, this assumption is neither sufficient nor necessary.

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