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Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data

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Gene Regulatory Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1883))

Abstract

A challenging problem in systems biology is the reconstruction of gene regulatory networks from postgenomic data. A variety of reverse engineering methods from machine learning and computational statistics have been proposed in the literature. However, deciding on the best method to adopt for a particular application or data set might be a confusing task. The present chapter provides a broad overview of state-of-the-art methods with an emphasis on conceptual understanding rather than a deluge of mathematical details, and the pros and cons of the various approaches are discussed. Guidance on practical applications with pointers to publicly available software implementations are included. The chapter concludes with a comprehensive comparative benchmark study on simulated data and a real-work application taken from the current plant systems biology.

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Author information

Authors and Affiliations

  1. Johann Bernoulli Institute, University of Groningen, Groningen, The Netherlands

    Marco Grzegorczyk

  2. Center for Computer Science, Universidade Federal do Rio Grande, Rio Grande, Brazil

    Andrej Aderhold

  3. School of Mathematics and Statistics, University of Glasgow, Glasgow, UK

    Dirk Husmeier

Authors
  1. Marco Grzegorczyk
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  2. Andrej Aderhold
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  3. Dirk Husmeier
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Corresponding author

Correspondence to Dirk Husmeier .

Editor information

Editors and Affiliations

  1. School of Informatics, University of Edinburgh, Edinburgh, UK

    Guido Sanguinetti

  2. Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium

    Vân Anh Huynh-Thu

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Grzegorczyk, M., Aderhold, A., Husmeier, D. (2019). Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data. In: Sanguinetti, G., Huynh-Thu, V. (eds) Gene Regulatory Networks. Methods in Molecular Biology, vol 1883. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8882-2_3

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  • DOI: https://doi.org/10.1007/978-1-4939-8882-2_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8881-5

  • Online ISBN: 978-1-4939-8882-2

  • eBook Packages: Springer Protocols

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