Integrating sequence, expression and interaction data to determine condition-specific miRNA regulation.

ABSTRACT:

Motivation

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. MiRNAs were shown to play an important role in development and disease, and accurately determining the networks regulated by these miRNAs in a specific condition is of great interest. Early work on miRNA target prediction has focused on using static sequence information. More recently, researchers have combined sequence and expression data to identify such targets in various conditions.

Results

We developed the Protein Interaction-based MicroRNA Modules (PIMiM), a regression-based probabilistic method that integrates sequence, expression and interaction data to identify modules of mRNAs controlled by small sets of miRNAs. We formulate an optimization problem and deve

SUBMITTER: Le HS 

PROVIDER: S-EPMC3694655 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature