Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs.

ABSTRACT:

Background

Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs) and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF) binding sites (TFBSs). Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed.

Results

We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinit

SUBMITTER: Girgis HZ 

PROVIDER: S-EPMC3359238 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature