Inferring the relation between transcriptional and posttranscriptional regulation from expression compendia.

ABSTRACT:

Background

Publicly available expression compendia that measure both mRNAs and sRNAs provide a promising resource to simultaneously infer the transcriptional and the posttranscriptional network. To maximally exploit the information contained in such compendia, we propose an analysis flow that combines publicly available expression compendia and sequence-based predictions to infer novel sRNA-target interactions and to reconstruct the relation between the sRNA and the transcriptional network.

Results

We relied on module inference to construct modules of coexpressed genes (sRNAs). TFs and sRNAs were assigned to these modules using the state-of-the-art inference techniques LeMoNe and Context Likelihood of Relatedness (CLR). Combining these expressions with sequence-based sRNA-ta

SUBMITTER: Ishchukov I 

PROVIDER: S-EPMC3948049 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature