Computational Statistics

, Volume 28, Issue 1, pp 19–36 | Cite as

Attractors in Boolean networks: a tutorial

  • Martin Hopfensitz
  • Christoph Müssel
  • Markus Maucher
  • Hans A. Kestler
Original Paper

Abstract

Boolean networks are a popular class of models for the description of gene-regulatory networks. They model genes as simple binary variables, being either expressed or not expressed. Simulations of Boolean networks can give insights into the dynamics of cellular systems. In particular, stable states and cycles in the networks are thought to correspond to phenotypes. This paper presents approaches to identify attractors in synchronous, asynchronous and probabilistic Boolean networks and gives examples of their usage in the BoolNet R package.

Keywords

Systems biology Boolean networks Attractors 

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Martin Hopfensitz
    • 1
  • Christoph Müssel
    • 1
  • Markus Maucher
    • 1
  • Hans A. Kestler
    • 1
  1. 1.Research Group Bioinformatics and Systems Biology, Institute of Neural Information ProcessingUniversity of UlmUlmGermany

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