Modeling gene-regulatory networks to describe cell fate transitions and predict master regulators.

ABSTRACT: Complex organisms originate from and are maintained by the information encoded in the genome. A major challenge of systems biology is to develop algorithms that describe the dynamic regulation of genome functions from large omics datasets. Here, we describe TETRAMER, which reconstructs gene-regulatory networks from temporal transcriptome data during cell fate transitions to predict "master" regulators by simulating cascades of temporal transcription-regulatory events.

SUBMITTER: Cholley PE 

PROVIDER: S-EPMC6070484 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature