Modeling gene-regulatory networks to describe cell fate transitions and predict master regulators
Journal article, 2018

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.

Author

Pierre-Etienne Cholley

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

University of Strasbourg

CSBI

Julien Moehlin

University of Strasbourg

Alexia Rohmer

University of Strasbourg

Vincent Zilliox

University of Strasbourg

Samuel Nicaise

University of Strasbourg

Hinrich Gronemeyer

University of Strasbourg

Marco Antonio Mendoza-Parra

Genomique Metabolique

University of Strasbourg

npj Systems Biology and Applications

20567189 (eISSN)

Vol. 4 1 29

Subject Categories

Developmental Biology

Bioinformatics (Computational Biology)

Bioinformatics and Systems Biology

DOI

10.1038/s41540-018-0066-z

More information

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