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On the Use of Temporal Formal Logic to Model Gene Regulatory Networks

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Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6160))

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Abstract

Modelling activities in molecular biology face the difficulty of prediction to link molecular knowledge with cell phenotypes. Even when the interaction graph between molecules is known, the deduction of the cellular dynamics from this graph remains a strong corner stone of the modelling activity, in particular one has to face the parameter identification problem. This article is devoted to convince the reader that computers can be used not only to simulate a model of the studied biological system but also to deduce the sets of parameter values that lead to a behaviour compatible with the biological knowledge (or hypotheses) about dynamics. This approach is based on formal logic. It is illustrated in the discrete modelling framework of genetic regulatory networks due to René Thomas.

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Authors and Affiliations

  1. Algorithmes-Euclide-B, Laboratoire I3S, UMR 6070 UNS-CNRS, 2000, route des Lucioles, B.P. 121, F-06903, Sophia Antipolis Cedex

    Gilles Bernot & Jean-Paul Comet

Authors
  1. Gilles Bernot
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  2. Jean-Paul Comet
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Editor information

Editors and Affiliations

  1. DISI - Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, Via Dodecaneso 35, 16146, Genova, Italy

    Francesco Masulli

  2. Center for Biostatistics, The Methodist Hospital Research Institute (TMHRI), Weill Cornell Medical College, Cornell University, 6565 Fannin, Suite MGJ6-031, 77030, Houston, Texas, USA

    Leif E. Peterson

  3. Dipartimento di Matematica ed Informatica, UniversitĂ  di Salerno, Via Ponte don Melillo, 84084, Fisciano, (Sa), Italy

    Roberto Tagliaferri

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Bernot, G., Comet, JP. (2010). On the Use of Temporal Formal Logic to Model Gene Regulatory Networks. In: Masulli, F., Peterson, L.E., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2009. Lecture Notes in Computer Science(), vol 6160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14571-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-14571-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14570-4

  • Online ISBN: 978-3-642-14571-1

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