Literature DB >> 27587700

Logical model specification aided by model-checking techniques: application to the mammalian cell cycle regulation.

Pauline Traynard1, Adrien Fauré2, François Fages3, Denis Thieffry1.   

Abstract

MOTIVATION: Understanding the temporal behaviour of biological regulatory networks requires the integration of molecular information into a formal model. However, the analysis of model dynamics faces a combinatorial explosion as the number of regulatory components and interactions increases.
RESULTS: We use model-checking techniques to verify sophisticated dynamical properties resulting from the model regulatory structure in the absence of kinetic assumption. We demonstrate the power of this approach by analysing a logical model of the molecular network controlling mammalian cell cycle. This approach enables a systematic analysis of model properties, the delineation of model limitations, and the assessment of various refinements and extensions based on recent experimental observations. The resulting logical model accounts for the main irreversible transitions between cell cycle phases, the sequential activation of cyclins, and the inhibitory role of Skp2, and further emphasizes the multifunctional role for the cell cycle inhibitor Rb.
AVAILABILITY AND IMPLEMENTATION: The original and revised mammalian cell cycle models are available in the model repository associated with the public modelling software GINsim (http://ginsim.org/node/189). CONTACT: thieffry@ens.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Mesh:

Year:  2016        PMID: 27587700     DOI: 10.1093/bioinformatics/btw457

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

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3.  Logical Modeling and Analysis of Cellular Regulatory Networks With GINsim 3.0.

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Journal:  Front Physiol       Date:  2018-06-19       Impact factor: 4.566

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  7 in total

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