Exploiting sequence-based features for predicting enhancer-promoter interactions.

ABSTRACT:

Motivation

A large number of distal enhancers and proximal promoters form enhancer-promoter interactions to regulate target genes in the human genome. Although recent high-throughput genome-wide mapping approaches have allowed us to more comprehensively recognize potential enhancer-promoter interactions, it is still largely unknown whether sequence-based features alone are sufficient to predict such interactions.

Results

Here, we develop a new computational method (named PEP) to predict enhancer-promoter interactions based on sequence-based features only, when the locations of putative enhancers and promoters in a particular cell type are given. The two modules in PEP (PEP-Motif and PEP-Word) use different but complementary feature extraction strategies to exploit sequence-b

SUBMITTER: Yang Y 

PROVIDER: S-EPMC5870728 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature