Stochastic Boolean Networks

David Murrugarra; Daniel Plaugher; Alan Veliz-Cuba

doi:10.1016/B978-0-443-29652-9.00012-9

Stochastic Boolean Networks

David Murrugarra
, Daniel Plaugher
, Alan Veliz-Cuba

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Stochasticity is a fundamental property of biological networks, and it can have a significant impact on the dynamics of these networks. To account for the stochasticity in various molecular processes, several versions of stochastic Boolean networks exist including probabilistic Boolean networks, perturbed Boolean networks, and probabilistic edge operators. This chapter will focus on the stochastic framework that is usually referred as Stochastic Discrete Dynamical Systems (SDDS). The SDDS framework introduces stochasticity by assigning propensity parameters for activation and degradation to each function in the Boolean network. We will describe how obtain information of the long-term dynamics of an SDDS as well as how to tune the propensity parameters. Finally, we will describe a toolbox for simulation using SDDS and discuss potential applications for the control and optimal control of discrete systems.

Original language	English
Title of host publication	Mathematical Concepts and Methods in Modern Biology
Subtitle of host publication	Using Modern Discrete Models
Pages	129-152
Number of pages	24
ISBN (Electronic)	9780443296529
DOIs	https://doi.org/10.1016/B978-0-443-29652-9.00012-9
State	Published - Jan 1 2026

Bibliographical note

Publisher Copyright:
© 2026 Elsevier Inc. All rights reserved.

Keywords

Genetic algorithms
Google PageRank
Markov decision processes
Optimal control
Propensity parameters
Stochastic discrete systems

ASJC Scopus subject areas

General Agricultural and Biological Sciences
General Biochemistry, Genetics and Molecular Biology

Access to Document

10.1016/B978-0-443-29652-9.00012-9

Cite this

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KW - Optimal control

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Stochastic Boolean Networks

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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