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Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling

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Gene Regulatory Networks

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

Abstract

Modelling gene regulatory networks requires not only a thorough understanding of the biological system depicted, but also the ability to accurately represent this system from a mathematical perspective. Throughout this chapter, we aim to familiarize the reader with the biological processes and molecular factors at play in the process of gene expression regulation. We first describe the different interactions controlling each step of the expression process, from transcription to mRNA and protein decay. In the second section, we provide statistical tools to accurately represent this biological complexity in the form of mathematical models. Among other considerations, we discuss the topological properties of biological networks, the application of deterministic and stochastic frameworks, and the quantitative modelling of regulation. We particularly focus on the use of such models for the simulation of expression data that can serve as a benchmark for the testing of network inference algorithms.

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Acknowledgements

We are very grateful for enriching discussions and suggestions on this manuscript made by Samantha Baldwin and Susan Thomson (Plant and Food Research, Lincoln, New Zealand). We would like to thank the reviewers of this chapter for their useful comments. MV was partly supported by a visiting professor scholarship from Aix-Marseille University.

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Correspondence to Matthieu Vignes .

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Angelin-Bonnet, O., Biggs, P.J., Vignes, M. (2019). Gene Regulatory Networks: A Primer in Biological Processes and Statistical Modelling. 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_15

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  • DOI: https://doi.org/10.1007/978-1-4939-8882-2_15

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