Base-pair resolution detection of transcription factor binding site by deep deconvolutional network.

ABSTRACT:

Motivation

Transcription factor (TF) binds to the promoter region of a gene to control gene expression. Identifying precise TF binding sites (TFBSs) is essential for understanding the detailed mechanisms of TF-mediated gene regulation. However, there is a shortage of computational approach that can deliver single base pair resolution prediction of TFBS.

Results

In this paper, we propose DeepSNR, a Deep Learning algorithm for predicting TF binding location at Single Nucleotide Resolution de novo from DNA sequence. DeepSNR adopts a novel deconvolutional network (deconvNet) model and is inspired by the similarity to image segmentation by deconvNet. The proposed deconvNet architecture is constructed on top of 'DeepBind' and we trained the entire model using TF-specific data from

SUBMITTER: Salekin S 

PROVIDER: S-EPMC6184544 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature