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Attractors in Boolean networks: a tutorial

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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.

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Correspondence to Hans A. Kestler.

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Martin Hopfensitz and Christoph Müssel contributed equally.

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Hopfensitz, M., Müssel, C., Maucher, M. et al. Attractors in Boolean networks: a tutorial. Comput Stat 28, 19–36 (2013). https://doi.org/10.1007/s00180-012-0324-2

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