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International Conference on Computational Methods in Systems Biology

CMSB 2017: Computational Methods in Systems Biology pp 309–316Cite as

Pint: A Static Analyzer for Transient Dynamics of Qualitative Networks with IPython Interface

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

Abstract

The software Pint is devoted to the scalable analysis of the traces of automata networks, which encompass Boolean and discrete networks. Pint implements formal approximations of transient reachability-related properties, including mutation prediction and model reduction.

Pint is distributed with command line tools, as well as a Python module pypint. The latter provides a seamless integration with the Jupyter IPython notebook web interface, which allows to easily save, reuse, reproduce, and share workflows of model analysis.

Pint can address networks with hundreds to thousands interacting components, which are typically intractable with standard approaches.

This work was supported by ANR-FNR project “AlgoReCell” (ANR-16-CE12-0034) and by CNRS PEPS INS2I 2017 project “FoRCe”.

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Notes

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Authors and Affiliations

  1. CNRS, LRI UMR 8623, Univ. Paris-Sud – CNRS, Université Paris-Saclay, 91405, Orsay, France

    Loïc Paulevé

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  1. Loïc Paulevé
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Correspondence to Loïc Paulevé .

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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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Paulevé, L. (2017). Pint: A Static Analyzer for Transient Dynamics of Qualitative Networks with IPython Interface. 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_20

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  • DOI: https://doi.org/10.1007/978-3-319-67471-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67470-4

  • Online ISBN: 978-3-319-67471-1

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