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Random Boolean network models and the yeast transcriptional network.


ABSTRACT: The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that, for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state, regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.

SUBMITTER: Kauffman S 

PROVIDER: S-EPMC299805 | biostudies-literature | 2003 Dec

REPOSITORIES: biostudies-literature

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Random Boolean network models and the yeast transcriptional network.

Kauffman Stuart S   Peterson Carsten C   Samuelsson Björn B   Troein Carl C  

Proceedings of the National Academy of Sciences of the United States of America 20031201 25


The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that, for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense  ...[more]

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