Literature DB >> 10235650

The modularity of biological regulatory networks.

D Thieffry1, D Romero.   

Abstract

A useful approach to complex regulatory networks consists of modeling their elements and interactions by Boolean equations. In this context, feedback circuits (i.e. circular sequences of interactions) have been shown to play key dynamical roles: whereas positive circuits are able to generate multistationarity, negative circuits may generate oscillatory behavior. In this paper, we principally focus on the case of gene networks. These are represented by fully connected Boolean networks where each element interacts with all elements including itself. Flexibility in network design is introduced by the use of Boolean parameters, one associated with each interaction or group of interactions affecting a given element. Within this formalism, a feedback circuit will generate its typical dynamical behavior (i.e. multistationarity or oscillations) only for appropriate values of some of the logical parameters. Whenever it does, we say that the circuit is 'functional'. More interestingly, this formalism allows the computation of the constraints on the logical parameters to have any feedback circuit functional in a network. Using this methodology, we found that the fraction of the total number of consistent combinations of parameter values that make a circuit functional decreases geometrically with the circuit length. From a biological point of view, this suggests that regulatory networks could be decomposed into small and relatively independent feedback circuits or 'regulatory modules'.

Mesh:

Year:  1999        PMID: 10235650     DOI: 10.1016/s0303-2647(98)00087-2

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  15 in total

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Review 7.  Multi-parameter exploration of dynamics of regulatory networks.

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Journal:  FEMS Microbiol Rev       Date:  2009-01       Impact factor: 16.408

10.  Functional architecture of Escherichia coli: new insights provided by a natural decomposition approach.

Authors:  Julio A Freyre-González; José A Alonso-Pavón; Luis G Treviño-Quintanilla; Julio Collado-Vides
Journal:  Genome Biol       Date:  2008-10-27       Impact factor: 13.583

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