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Detecting Attractors in Biological Models with Uncertain Parameters

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Computational Methods in Systems Biology (CMSB 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10545))

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Abstract

Complex behaviour arising in biological systems is typically characterised by various kinds of attractors. An important problem in this area is to determine these attractors. Biological systems are usually described by highly parametrised dynamical models that can be represented as parametrised graphs typically constructed as discrete abstractions of continuous-time models. In such models, attractors are observed in the form of terminal strongly connected components (tSCCs). In this paper, we introduce a novel method for detecting tSCCs in parametrised graphs. The method is supplied with a parallel algorithm and evaluated on discrete abstractions of several non-linear biological models.

This work has been supported by the Czech Science Foundation grant GA15-11089S and by the Czech National Infrastructure grant LM2015055.

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Authors and Affiliations

  1. Systems Biology Laboratory, Faculty of Informatics, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Jiří Barnat, Nikola Beneš, Luboš Brim, Martin Demko, Matej Hajnal, Samuel Pastva & David Šafránek

Authors
  1. Jiří Barnat
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  2. Nikola Beneš
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  3. Luboš Brim
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  4. Martin Demko
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  5. Matej Hajnal
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  6. Samuel Pastva
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  7. David Šafránek
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Correspondence to Nikola Beneš .

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Editors and Affiliations

  1. Inria & École normale supérieure, Paris, France

    Jérôme Feret

  2. Technische Universität Darmstadt, Darmstadt, Germany

    Heinz Koeppl

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Barnat, J. et al. (2017). Detecting Attractors in Biological Models with Uncertain Parameters. In: Feret, J., Koeppl, H. (eds) Computational Methods in Systems Biology. CMSB 2017. Lecture Notes in Computer Science(), vol 10545. Springer, Cham. https://doi.org/10.1007/978-3-319-67471-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-67471-1_3

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