Phenotype Control techniques for Boolean gene regulatory networks

Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting...

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Bibliographic Details
Published in:Bulletin of mathematical biology Vol. 85; no. 10; p. 89
Main Authors: Plaugher, Daniel, Murrugarra, David
Format: Journal Article
Language:English
Published: New York Springer US 01.10.2023
Springer Nature B.V
Subjects:
Boolean
Boolean algebra
Boolean functions
Cancer
Cell Biology
Control theory
Feedback
Gene Regulatory Networks
Genotype & phenotype
Leukemia
Life Sciences
Lymphocytes
Lymphocytes T
Mathematical and Computational Biology
Mathematical Concepts
Mathematics
Mathematics and Statistics
Models, Biological
Modularity
Networks
Ordinary differential equations
Partial differential equations
Phenotype
Phenotypes
Review
Signal transduction
Software
Vertex sets
Cuba
Network dynamics
Phenotype control theory
Regulatory networks
Discrete dynamical systems
Boolean networks
ISSN:0092-8240, 1522-9602, 1522-9602
Online Access:Get full text
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Summary:Modeling cell signal transduction pathways via Boolean networks (BNs) has become an established method for analyzing intracellular communications over the last few decades. What’s more, BNs provide a course-grained approach, not only to understanding molecular communications, but also for targeting pathway components that alter the long-term outcomes of the system. This has come to be known as phenotype control theory . In this review we study the interplay of various approaches for controlling gene regulatory networks such as: algebraic methods, control kernel, feedback vertex set, and stable motifs. The study will also include comparative discussion between the methods, using an established cancer model of T-Cell Large Granular Lymphocyte Leukemia. Further, we explore possible options for making the control search more efficient using reduction and modularity. Finally, we will include challenges presented such as the complexity and the availability of software for implementing each of these control techniques.
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ISSN:0092-8240
1522-9602
1522-9602
DOI:10.1007/s11538-023-01197-6