Random Boolean network models and the yeast transcriptional network

Research output: Contribution to journalArticle


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.


  • Stuart Kauffman
  • Carsten Peterson
  • Björn Samuelsson
  • Carl Troein
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Zoology
  • Biophysics


  • genetic networks, dynamical systems
Original languageEnglish
Pages (from-to)14796-14799
JournalProceedings of the National Academy of Sciences
Issue number25
Publication statusPublished - 2003
Publication categoryResearch

Related research output

Samuelsson, B., 2006, Department of Theoretical Physics, Lund University. 117 p.

Research output: ThesisDoctoral Thesis (compilation)

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