Boolean Networks as Predictive Models of Emergent Biological Behaviors

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Jordan C. Rozum (Binghamton University, State University of New York) Colin Campbell (University of Mount Union)

Boolean Networks as Predictive Models of Emergent Biological Behaviors

Jordan C. Rozum (Binghamton University, State University of New York), Colin Campbell (University of Mount Union), Eli Newby (Pennsylvania State University) , Fatemeh Sadat Fatemi Nasrollahi (Indiana University)

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English

Cambridge University Press
28 March 2024

Discrete mathematics; Algebra; Mathematical modelling; Biology, life sciences

Series: Elements in the Structure and Dynamics of Complex Networks

Summary
Details

Interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions – from molecules in gene regulatory networks to species in ecological networks – and the often-incomplete state of system knowledge, such as the unknown values of kinetic parameters for biochemical reactions. Boolean networks have emerged as a powerful tool for modeling these systems. This Element provides a methodological overview of Boolean network models of biological systems. After a brief introduction, the authors describe the process of building, analyzing, and validating a Boolean model. They then present the use of the model to make predictions about the system's response to perturbations and about how to control its behavior. The Element emphasizes the interplay between structural and dynamical properties of Boolean networks and illustrates them in three case studies from disparate levels of biological organization.

By: Jordan C. Rozum (Binghamton University State University of New York), Colin Campbell (University of Mount Union), Eli Newby (Pennsylvania State University), Fatemeh Sadat Fatemi Nasrollahi (Indiana University), Réka Albert (Pennsylvania State University)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Weight: 125g
ISBN: 9781009292962
ISBN 10: 100929296X
Series: Elements in the Structure and Dynamics of Complex Networks
Pages: 68
Publication Date: 28 March 2024
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active