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

Date publication

janvier 2018

Journal

NPJ systems biology and applications

Auteurs

Membres identifiés du Cancéropôle Est :
Dr GRONEMEYER Hinrich

Tous les auteurs :
Cholley PE, Moehlin J, Rohmer A, Zilliox V, Nicaise S, Gronemeyer H, Mendoza-Parra MA

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/30083390

Résumé

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.

Référence

NPJ Syst Biol Appl. 2018 ;4:29