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Logical Modelling of Gene Regulatory Networks with GINsim

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Bacterial Molecular Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 804))

Abstract

Discrete mathematical formalisms are well adapted to model large biological networks, for which detailed kinetic data are scarce. This chapter introduces the reader to a well-established qualitative (logical) framework for the modelling of regulatory networks. Relying on GINsim, a software implementing this logical formalism, we guide the reader step by step towards the definition and the analysis of a simple model of the lysis–lysogeny decision in the bacteriophage λ.

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Acknowledgments

A.N. has been supported by a PhD grant from the French Ministry of Research and Technology. This project was further supported by research grants from the EU FP6 (DIAMONDS STREP) and FP7 (APOSYS large scale project) programs, and by the Belgian Science Policy Office (IAP BioMaGNet).

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Authors and Affiliations

  1. Instituto Gulbenkian de Ciência, Oeiras, Portugal

    Claudine Chaouiya

  2. TAGC, INSERM U928, Marseille, France

    Aurélien Naldi

  3. Institut de Biologie de l’Ecole Normale Supérieure (IBENS), UMR ENS, CNRS 8197, INSERM 1024, Paris, France

    Denis Thieffry

Authors
  1. Claudine Chaouiya
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  2. Aurélien Naldi
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  3. Denis Thieffry
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Corresponding author

Correspondence to Claudine Chaouiya .

Editor information

Editors and Affiliations

  1. Labo. Bioinformatique des, Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, bd. du Triomphe, Bruxelles, 1050, Belgium

    Jacques van Helden

  2. Labo. Bioinformatique des, Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, Bvd. du Triomphe, Bruxelles, 1050, Belgium

    Ariane Toussaint

  3. INSERM 1024, Institut de Biologie de l'Ecole Normale, rue d'Ulm 46, Paris, 75230, France

    Denis Thieffry

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Chaouiya, C., Naldi, A., Thieffry, D. (2012). Logical Modelling of Gene Regulatory Networks with GINsim. In: van Helden, J., Toussaint, A., Thieffry, D. (eds) Bacterial Molecular Networks. Methods in Molecular Biology, vol 804. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-361-5_23

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  • DOI: https://doi.org/10.1007/978-1-61779-361-5_23

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-61779-360-8

  • Online ISBN: 978-1-61779-361-5

  • eBook Packages: Springer Protocols

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