Computing Symbolic Steady States of Boolean Networks

Please always quote using this URN:urn:nbn:de:0296-matheon-12823
  • 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. In 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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Metadaten
Author:Hannes Klarner, Alexander Bockmayr, Heike Siebert
URN:urn:nbn:de:0296-matheon-12823
Referee:Peter Deuflhard
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2014/04/15
Release Date:2014/04/15
Tag:Boolean network; biological network; discrete dynamical system; prime implicand
Institute:Research Center Matheon
Freie Universität Berlin
MSC-Classification:92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Cxx Physiological, cellular and medical topics / 92C42 Systems biology, networks
Preprint Number:1056
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