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Random Boolean network models and the yeast transcriptional network

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Author

Summary, in English

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.

Publishing year

2003

Language

English

Pages

14796-14799

Publication/Series

Proceedings of the National Academy of Sciences

Volume

100

Issue

25

Document type

Journal article

Publisher

National Academy of Sciences

Topic

  • Zoology
  • Biophysics

Keywords

  • genetic networks
  • dynamical systems

Status

Published

ISBN/ISSN/Other

  • ISSN: 1091-6490