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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Bulletin of mathematical biology Jg. 85; H. 10; S. 89
Hauptverfasser:	Plaugher, Daniel, Murrugarra, David
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2023 Springer Nature B.V
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Review-3 content type line 23
ISSN:	0092-8240 1522-9602 1522-9602
DOI:	10.1007/s11538-023-01197-6