×

Abstract interpretation of dynamics of biological regulatory networks. (English) Zbl 1291.92069

Feret, J. (ed.) et al., Proceedings of the 1st international workshop on static analysis and systems biology (SASB 2010), Perpignan, France, September 13, 2010. Amsterdam: Elsevier. Electronic Notes in Theoretical Computer Science 272, 43-56 (2011).
Summary: Analysing dynamics of large biological regulatory networks (BRNs) calls for innovative methods to cope with the state space explosion. Static analysis and abstract interpretation techniques seem promising approaches. In this paper, we address the process hitting framework, that has been shown of interest to model dynamics of BRNs with discrete values. We propose to take profit from the particular structures of process hitting to build efficient static analyses. We introduce a novel and original method to decide the reachability of the state of a component within a BRN modelled in process hitting. The decision is achieved by abstract interpretation and static analysis of process hittings. The scalability of our approach is illustrated by its application to the analysis of a BRN with 40 components.
For the entire collection see [Zbl 1283.92003].

MSC:

92C42 Systems biology, networks
68Q60 Specification and verification (program logics, model checking, etc.)

Software:

libDDD
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Aracena, J., Maximum number of fixed points in regulatory boolean networks, Bulletin of Mathematical Biology, 70, 1398-1409 (2008) · Zbl 1144.92323
[2] Bernot, G.; Cassez, F.; Comet, J.-P.; Delaplace, F.; Müller, C.; Roux, O., Semantics of biological regulatory networks, Electronic Notes in Theoretical Computer Science, 180, 3-14 (2007)
[3] Bernot, G., J.-P. Comet and Z. Khalis, Gene regulatory networks with multiplexesEuropean Simulation and Modelling Conference Proceedings; Bernot, G., J.-P. Comet and Z. Khalis, Gene regulatory networks with multiplexesEuropean Simulation and Modelling Conference Proceedings
[4] Klamt, S.; Saez-Rodriguez, J.; Lindquist, J.; Simeoni, L.; Gilles, E., A methodology for the structural and functional analysis of signaling and regulatory networks, BMC Bioinformatics, 7, 56 (2006)
[5] LIP6/Move, the libDDD environmenthttp://ddd.lip6.fr; LIP6/Move, the libDDD environmenthttp://ddd.lip6.fr
[6] Naldi, A.; Thieffry, D.; Chaouiya, C., Computational Methods in Systems Biology (2007), pp. 233-247
[7] Paulevé, L., M. Magnin and O. Roux, Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus FrameworkTo appearhttp://www.irccyn.ec-nantes.fr/ pauleve/refining-revised.pdf; Paulevé, L., M. Magnin and O. Roux, Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus FrameworkTo appearhttp://www.irccyn.ec-nantes.fr/ pauleve/refining-revised.pdf
[8] Remy, É.; Ruet, P.; Thieffry, D., Graphic requirements for multistability and attractive cycles in a boolean dynamical framework, Advances in Applied Mathematics, 41, 335-350 (2008) · Zbl 1169.05333
[9] Richard, A.; Comet, J.-P., Necessary conditions for multistationarity in discrete dynamical systems, Discrete Applied Mathematics, 155, 2403-2413 (2007) · Zbl 1125.37062
[10] Richard, A.; Comet, J.-P.; Bernot, G., Modern Formal Methods and Applications (2006), pp. 83-122
[11] Thomas, R., Boolean formalization of genetic control circuits, Journal of Theoretical Biology, 42, 563-585 (1973)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.