Encyclopedia of Systems Biology

2013 Edition
| Editors: Werner Dubitzky, Olaf Wolkenhauer, Kwang-Hyun Cho, Hiroki Yokota

Probabilistic Boolean Networks

Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-9863-7_380

Definition

A probabilistic Boolean network (PBN) is essentially a set of discrete collection of Boolean networks (BNs) in which at any discrete time point the state vector transforms according to the rules of one of the Boolean networks (Shmulevich et al. 2002).

There are two classes of PBN models: synchronous PBNs and asynchronous PBNs, depending on whether or not the states of nodes are updated synchronously. Synchronous model is more popular and easier to analyze and therefore we adopt it in our discussion.

Among the synchronous PBNs, there are two types of PBNs: instantaneously random PBNs and context-sensitive PBNs. In an instantaneously random PBN, the governing Boolean network is randomly chosen at each time point, which means that the rule for updating each gene is randomly chosen at each time step from several possible rules in accordance with a fixed probability distribution. The context-sensitive PBN is an extension of PBN. It differs from PBN for two reasons: (1) Each gene...

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References

  1. Pal R, Datta A, Bittner M, Dougherty E (2005) Intervention in context-sensitive probabilistic Boolean networks. Bioinformatics 21:1211–1218PubMedGoogle Scholar
  2. Shmulevich I, Dougherty E (2007) Genomic signal processing. Princeton University Press, PrincetonGoogle Scholar
  3. Shmulevich I, Dougherty E, Kim S, Zhang W (2002) From Boolean to probabilistic Boolean networks as models of genetic regulatory networks. In: Proceedings of the IEEE, vol 90, pp 1778–1792Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.Advanced Modeling and Applied Computing Laboratory, Department of MathematicsUniversity of Hong KongHong KongChina
  2. 2.Department of MathematicsAdvanced Modeling and Applied Computing Laboratory, The University of Hong KongHong KongChina
  3. 3.Department of MathematicsAdvanced Modeling and Applied Computing Laboratory, The University of Hong KongHong KongChina