Computing Symbolic Steady States of Boolean Networks

  • Hannes Klarner
  • Alexander Bockmayr
  • Heike Siebert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8751)


Asymptotic behavior is often of particular interest when analyzing asynchronous Boolean networks representing biological systems such as signal transduction or gene regulatory networks. Methods based on a generalization of the steady state notion, the so-called symbolic steady states, can be exploited to investigate attractor properties as well as for model reduction techniques conserving attractors. In this paper, we propose a novel optimization-based method for computing all maximal symbolic steady states and motivate their use. n particular, we add a new result yielding a lower bound for the number of cyclic attractors and illustrate the methods with a short study of a MAPK pathway model.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hannes Klarner
    • 1
  • Alexander Bockmayr
    • 1
  • Heike Siebert
    • 1
  1. 1.FB Mathematik und InformatikFreie Universität BerlinBerlinGermany

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