Computing Symbolic Steady States of Boolean Networks
Autor: | Hannes Klarner, Heike Siebert, Alexander Bockmayr |
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Rok vydání: | 2014 |
Předmět: | |
Zdroj: | Lecture Notes in Computer Science ISBN: 9783319115191 ACRI |
DOI: | 10.1007/978-3-319-11520-7_59 |
Popis: | 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. |
Databáze: | OpenAIRE |
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