Modeling the dynamic behavior of biochemical regulatory networks

JOURNAL OF THEORETICAL BIOLOGY

卷:462

Article

Tyson, John J.^1,2  Laomettachit, Teeraphan³  Kraikivski, Pavel^1,2 

[1] Virginia Tech, Dept Biol Sci, 5088 Derring Hall, Blacksburg, VA 24061 USA

[2] Virginia Tech, Acad Integrated Sci, Div Syst Biol, Blacksburg, VA 24061 USA

[3] King Mongkuts Univ Technol Thonburi, Bioinformat & Syst Biol Program, Bangkok 10150, Thailand

关键词: Molecular regulatory networks;    Signaling motifs;    Logical models;    Dynamic models;    Stochastic models;    Piecewise-linear odes;    Bifurcation theory;   

DOI  :  10.1016/j.jtbi.2018.11.034

来源: Elsevier

【 摘 要 】

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. (C) 2018 Elsevier Ltd. All rights reserved.

【 授权许可】

Free