Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data.

ABSTRACT: Transcription factors (TFs) play crucial roles in regulating gene expression through interactions with specific DNA sequences. Recently, the sequence motif of almost 400 human TFs have been identified using high-throughput SELEX sequencing. However, there remain a large number of TFs (∼800) with no high-throughput-derived binding motifs. Computational methods capable of associating known motifs to such TFs will avoid tremendous experimental efforts and enable deeper understanding of transcriptional regulatory functions. We present a method to associate known motifs to TFs (MATLAB code is available in Supplementary Materials). Our method is based on a probabilistic framework that not only exploits DNA-binding domains and specificities, but also integrates open chromatin, gene expression and

SUBMITTER: Zamanighomi M 

PROVIDER: S-EPMC5449588 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature