Theoretical and computational tools to model multistable gene regulatory networks.
biophysics
computational modeling
gene regulatory network
genetic circuit
multi-stability
Journal
Reports on progress in physics. Physical Society (Great Britain)
ISSN: 1361-6633
Titre abrégé: Rep Prog Phys
Pays: England
ID NLM: 19620690R
Informations de publication
Date de publication:
22 08 2023
22 08 2023
Historique:
received:
13
02
2023
accepted:
02
08
2023
pmc-release:
22
08
2024
medline:
23
8
2023
pubmed:
3
8
2023
entrez:
2
8
2023
Statut:
epublish
Résumé
The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.
Identifiants
pubmed: 37531952
doi: 10.1088/1361-6633/acec88
pmc: PMC10521208
mid: NIHMS1926500
doi:
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIAMS NIH HHS
ID : R01 AR079150
Pays : United States
Organisme : NIAMS NIH HHS
ID : U01 AR073159
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
© 2023 IOP Publishing Ltd.
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