Critical slowing down in biochemical networks with feedback
Autor: | Curtis Peterson, Tommy A. Byrd, Andrew Mugler, Amir Erez, Robert Vogel, Michael Vennettilli, Grégoire Altan-Bonnet |
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Rok vydání: | 2019 |
Předmět: |
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Physiological Physics Stochastic modelling Response time Parameter space Renormalization group Models Biological 01 natural sciences Article 010305 fluids & plasmas Kinetics Bifurcation theory Hysteresis (economics) 0103 physical sciences Ising model Statistical physics 010306 general physics Scaling |
Zdroj: | Phys Rev E |
ISSN: | 2470-0053 2470-0045 |
Popis: | Near a bifurcation point, the response time of a system is expected to diverge due to the phenomenon of critical slowing down. We investigate critical slowing down in well-mixed stochastic models of biochemical feedback by exploiting a mapping to the mean-field Ising universality class. We analyze the responses to a sudden quench and to continuous driving in the model parameters. In the latter case, we demonstrate that our class of models exhibits the Kibble-Zurek collapse, which predicts the scaling of hysteresis in cellular responses to gradual perturbations. We discuss the implications of our results in terms of the tradeoff between a precise and a fast response. Finally, we use our mapping to quantify critical slowing down in T cells, where the addition of a drug is equivalent to a sudden quench in parameter space. |
Databáze: | OpenAIRE |
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