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.
Author: | Hannes Klarner, Alexander Bockmayr, Heike Siebert |
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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 |