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Characterization of Reachable Attractors Using Petri Net Unfoldings

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Computational Methods in Systems Biology (CMSB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8859))

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Abstract

Attractors of network dynamics represent the long-term behaviours of the modelled system. Their characterization is therefore crucial for understanding the response and differentiation capabilities of a dynamical system. In the scope of qualitative models of interaction networks, the computation of attractors reachable from a given state of the network faces combinatorial issues due to the state space explosion.

In this paper, we present a new algorithm that exploits the concurrency between transitions of parallel acting components in order to reduce the search space. The algorithm relies on Petri net unfoldings that can be used to compute a compact representation of the dynamics. We illustrate the applicability of the algorithm with Petri net models of cell signalling and regulation networks, Boolean and multi-valued. The proposed approach aims at being complementary to existing methods for deriving the attractors of Boolean models, while being generic since it applies to any safe Petri net.

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Author information

Authors and Affiliations

  1. LSV, ENS Cachan, INRIA, CNRS, France

    Thomas Chatain, Stefan Haar, Loïg Jezequel & Stefan Schwoon

  2. CNRS & Laboratoire de Recherche en Informatique UMR CNRS 8623, Université Paris-Sud, 91405, Orsay Cedex, France

    Loïc Paulevé

  3. team AMIB, Inria Saclay - Ile de France, Palaiseau, France

    Loïc Paulevé

Authors
  1. Thomas Chatain
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  2. Stefan Haar
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  3. Loïg Jezequel
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  4. Loïc Paulevé
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  5. Stefan Schwoon
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Editor information

Editors and Affiliations

  1. Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, M1 7DN, Manchester, UK

    Pedro Mendes , Joseph O. Dada  & Kieran Smallbone ,  & 

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Chatain, T., Haar, S., Jezequel, L., Paulevé, L., Schwoon, S. (2014). Characterization of Reachable Attractors Using Petri Net Unfoldings. In: Mendes, P., Dada, J.O., Smallbone, K. (eds) Computational Methods in Systems Biology. CMSB 2014. Lecture Notes in Computer Science(), vol 8859. Springer, Cham. https://doi.org/10.1007/978-3-319-12982-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-12982-2_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12981-5

  • Online ISBN: 978-3-319-12982-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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