On Robustness Computation and Optimization in BIOCHAM-4

François Fages; Sylvain Soliman

doi:10.1007/978-3-319-99429-1_18

On Robustness Computation and Optimization in BIOCHAM-4

François Fages, Sylvain Soliman

INRIA

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Computational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings
Editors	David Safranek, Milan Ceska
Publisher	Springer Verlag
Pages	292-299
Number of pages	8
ISBN (Print)	9783319994284
DOIs	https://doi.org/10.1007/978-3-319-99429-1_18
Publication status	Published - 1 Jan 2018
Externally published	Yes
Event	16th International Conference on Computational Methods in Systems Biology, CMSB 2018 - Brno, Czech Republic Duration: 12 Sept 2018 → 14 Sept 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11095 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Computational Methods in Systems Biology, CMSB 2018
Country/Territory	Czech Republic
City	Brno
Period	12/09/18 → 14/09/18

Access to Document

10.1007/978-3-319-99429-1_18

Cite this

Fages, F., & Soliman, S. (2018). On Robustness Computation and Optimization in BIOCHAM-4. In D. Safranek, & M. Ceska (Eds.), Computational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings (pp. 292-299). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11095 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-99429-1_18

Fages, François ; Soliman, Sylvain. / On Robustness Computation and Optimization in BIOCHAM-4. Computational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings. editor / David Safranek ; Milan Ceska. Springer Verlag, 2018. pp. 292-299 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "On Robustness Computation and Optimization in BIOCHAM-4",

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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Fages, F & Soliman, S 2018, On Robustness Computation and Optimization in BIOCHAM-4. in D Safranek & M Ceska (eds), Computational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11095 LNBI, Springer Verlag, pp. 292-299, 16th International Conference on Computational Methods in Systems Biology, CMSB 2018, Brno, Czech Republic, 12/09/18. https://doi.org/10.1007/978-3-319-99429-1_18

On Robustness Computation and Optimization in BIOCHAM-4. / Fages, François; Soliman, Sylvain.
Computational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings. ed. / David Safranek; Milan Ceska. Springer Verlag, 2018. p. 292-299 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11095 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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