Literature DB >> 23188157

Deconstruction and dynamical robustness of regulatory networks: application to the yeast cell cycle networks.

Eric Goles1, Marco Montalva, Gonzalo A Ruz.   

Abstract

Analyzing all the deterministic dynamics of a Boolean regulatory network is a difficult problem since it grows exponentially with the number of nodes. In this paper, we present mathematical and computational tools for analyzing the complete deterministic dynamics of Boolean regulatory networks. For this, the notion of alliance is introduced, which is a subconfiguration of states that remains fixed regardless of the values of the other nodes. Also, equivalent classes are considered, which are sets of updating schedules which have the same dynamics. Using these techniques, we analyze two yeast cell cycle models. Results show the effectiveness of the proposed tools for analyzing update robustness as well as the discovery of new information related to the attractors of the yeast cell cycle models considering all the possible deterministic dynamics, which previously have only been studied considering the parallel updating scheme.

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Year:  2012        PMID: 23188157     DOI: 10.1007/s11538-012-9794-1

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  4 in total

1.  Logical Reduction of Biological Networks to Their Most Determinative Components.

Authors:  Mihaela T Matache; Valentin Matache
Journal:  Bull Math Biol       Date:  2016-07-14       Impact factor: 1.758

2.  Influence maximization in Boolean networks.

Authors:  Thomas Parmer; Luis M Rocha; Filippo Radicchi
Journal:  Nat Commun       Date:  2022-06-16       Impact factor: 17.694

3.  Neutral space analysis for a Boolean network model of the fission yeast cell cycle network.

Authors:  Gonzalo A Ruz; Tania Timmermann; Javiera Barrera; Eric Goles
Journal:  Biol Res       Date:  2014-11-25       Impact factor: 5.612

Review 4.  Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models.

Authors:  Matteo Barberis; Robert G Todd; Lucas van der Zee
Journal:  FEMS Yeast Res       Date:  2016-12-18       Impact factor: 2.796

  4 in total

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