Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape.

ABSTRACT:

Motivation

An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem.

Results

Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding a

SUBMITTER: Dai H 

PROVIDER: S-EPMC5870668 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature