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On Robustness Computation and Optimization in BIOCHAM-4

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Computational Methods in Systems Biology (CMSB 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11095))

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Abstract

BIOCHAM-4 is a tool for modeling, analyzing and synthesizing biochemical reaction networks with respect to some formal, yet possibly imprecise, specification of their behavior. We focus here on one new capability of this tool to optimize the robustness of a parametric model with respect to a specification of its dynamics in quantitative temporal logic. More precisely, we present two complementary notions of robustness: the statistical notion of model robustness to parameter perturbations, defined as its mean functionality, and a metric notion of formula satisfaction robustness, defined as the penetration depth in the validity domain of the temporal logic constraints. We show how the formula robustness can be used in BIOCHAM-4 with no extra cost as an objective function in the parameter optimization procedure, to actually improve the model robustness. We illustrate these unique features with a classical example of the hybrid systems community and provide some performance figures on a model of MAPK signalling with 37 parameters.

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Notes

  1. 1.

    http://lifeware.inria.fr/biocham4.

  2. 2.

    https://lifeware.inria.fr/wiki/Main/Software#CMSB18.

  3. 3.

    http://www.bugseng.com/ppl.

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Acknowledgment

This work benefited from partial support from the ANR project HYCLOCK contract DS0401.

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Authors and Affiliations

  1. Inria Saclay - Ile de France, Lifeware Group, Palaiseau, France

    François Fages & Sylvain Soliman

Authors
  1. François Fages
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  2. Sylvain Soliman
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Corresponding author

Correspondence to François Fages .

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Editors and Affiliations

  1. Brno University of Technology, Brno, Czech Republic

    Milan Češka

  2. Masaryk University, Brno, Czech Republic

    David Šafránek

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Fages, F., Soliman, S. (2018). On Robustness Computation and Optimization in BIOCHAM-4. In: Češka, M., Šafránek, D. (eds) Computational Methods in Systems Biology. CMSB 2018. Lecture Notes in Computer Science(), vol 11095. Springer, Cham. https://doi.org/10.1007/978-3-319-99429-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-99429-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99428-4

  • Online ISBN: 978-3-319-99429-1

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