Phenotype control techniques for Boolean gene regulatory networks. (English) Zbl 07742019

Plaugher, Daniel; Murrugarra, David

Bull. Math. Biol. 85, No. 10, Paper No. 89, 36 p. (2023).

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.

MSC:

92C40	Biochemistry, molecular biology
92C42	Systems biology, networks
92C32	Pathology, pathophysiology
92-02	Research exposition (monographs, survey articles) pertaining to biology

Keywords:

discrete dynamical systems; network dynamics; regulatory networks; phenotype control theory; Boolean networks

Software:

Macaulay2; ADAM

References:

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