Data- and knowledge-based modeling of gene regulatory networks: an update

Authors

  • Jörg Linde Research Group Systems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstr. 11a, 07745 Jena, Germany
  • Sylvie Schulze Research Group Systems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstr. 11a, 07745 Jena, Germany
  • Sebastian G. Henkel BioControl Jena GmbH, Wildenbruchstr. 15, 07745 Jena, Germany
  • Reinhard Guthke Research Group Systems Biology / Bioinformatics, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Beutenbergstr. 11a, 07745 Jena, Germany

DOI:

https://doi.org/10.17179/excli2015-168

Keywords:

gene regulatory networks, modeling, reverse engineering, network inference, prior knowledge, RNA-Seq

Abstract

Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network inference methods focusing on novel techniques for data acquisition, network inference assessment, network inference for interacting species and the integration of prior knowledge. After the advance of Next-Generation-Sequencing of cDNAs derived from RNA samples (RNA-Seq) we discuss in detail its application to network inference. Furthermore, we present progress for large-scale or even full-genomic network inference as well as for small-scale condensed network inference and review advances in the evaluation of network inference methods by crowdsourcing. Finally, we reflect the current availability of data and prior knowledge sources and give an outlook for the inference of gene regulatory networks that reflect interacting species, in particular pathogen-host interactions.

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Published

2015-03-02

How to Cite

Linde, J., Schulze, S., Henkel, S. G., & Guthke, R. (2015). Data- and knowledge-based modeling of gene regulatory networks: an update. EXCLI Journal, 14, 346–378. https://doi.org/10.17179/excli2015-168

Issue

Vol. 14 (2015)

Section

Review articles

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