NetProphet 2.0: mapping transcription factor networks by exploiting scalable data resources.

ABSTRACT:

Motivation

Cells process information, in part, through transcription factor (TF) networks, which control the rates at which individual genes produce their products. A TF network map is a graph that indicates which TFs bind and directly regulate each gene. Previous work has described network mapping algorithms that rely exclusively on gene expression data and 'integrative' algorithms that exploit a wide range of data sources including chromatin immunoprecipitation sequencing (ChIP-seq) of many TFs, genome-wide chromatin marks, and binding specificities for many TFs determined in vitro. However, such resources are available only for a few major model systems and cannot be easily replicated for new organisms or cell types.

Results

We present NetProphet 2.0, a 'data light' algor

SUBMITTER: Kang Y 

PROVIDER: S-EPMC5860202 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature