Modeling the dynamic behavior of biochemical regulatory networks
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Publication Details
Author list: Tyson J.J., Laomettachit T., Kraikivski P.
Publisher: Elsevier
Publication year: 2019
Journal: Journal of Theoretical Biology (0022-5193)
Volume number: 462
Start page: 514
End page: 527
Number of pages: 14
ISSN: 0022-5193
Languages: English-Great Britain (EN-GB)
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Abstract
Strategies for modeling the complex dynamical behavior of gene/protein regulatory networks have evolved over the last 50 years as both the knowledge of these molecular control systems and the power of computing resources have increased. Here, we review a number of common modeling approaches, including Boolean (logical) models, systems of piecewise-linear or fully non-linear ordinary differential equations, and stochastic models (including hybrid deterministic/stochastic approaches). We discuss the pro's and con's of each approach, to help novice modelers choose a modeling strategy suitable to their problem, based on the type and bounty of available experimental information. We illustrate different modeling strategies in terms of some abstract network motifs, and in the specific context of cell cycle regulation. ฉ 2018 Elsevier Ltd
Keywords
Bifurcation theory, Dynamic models, Logical models, Molecular regulatory networks, Piecewise-linear odes, Signaling motifs, Stochastic models
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