BEESEM: estimation of binding energy models using HT-SELEX data.

ABSTRACT:

Motivation

Characterizing the binding specificities of transcription factors (TFs) is crucial to the study of gene expression regulation. Recently developed high-throughput experimental methods, including protein binding microarrays (PBM) and high-throughput SELEX (HT-SELEX), have enabled rapid measurements of the specificities for hundreds of TFs. However, few studies have developed efficient algorithms for estimating binding motifs based on HT-SELEX data. Also the simple method of constructing a position weight matrix (PWM) by comparing the frequency of the preferred sequence with single-nucleotide variants has the risk of generating motifs with higher information content than the true binding specificity.

Results

We developed an algorithm called BEESEM that builds on a co

SUBMITTER: Ruan S 

PROVIDER: S-EPMC5860122 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature