Control of Stochastic and Induced Switching in Biophysical Networks

Noise caused by fluctuations at the molecular level is a fundamental part of intracellular processes. While the response of biological systems to noise has been studied extensively, there has been limited understanding of how to exploit it to induce a desired cell state. Here we present a scalable,...

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Bibliographic Details
Published in:Physical review. X 2015-07, Vol.5 (3), p.031036, Article 031036
Main Authors: Wells, Daniel K, Kath, William L, Motter, Adilson E
Format: Article
Language:English
Subjects:
Algorithms
Apoptosis
Cancer
Cell death
Control methods
Differentiation (biology)
Gene expression
Networks
Noise
Noise control
Noise prediction
Parameter identification
Switching
Target recognition
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Summary:Noise caused by fluctuations at the molecular level is a fundamental part of intracellular processes. While the response of biological systems to noise has been studied extensively, there has been limited understanding of how to exploit it to induce a desired cell state. Here we present a scalable, quantitative method based on the Freidlin-Wentzell action to predict and control noise-induced switching between different states in genetic networks that, conveniently, can also control transitions between stable states in the absence of noise. We apply this methodology to models of cell differentiation and show how predicted manipulations of tunable factors can induce lineage changes, and further utilize it to identify new candidate strategies for cancer therapy in a cell death pathway model. This framework offers a systems approach to identifying the key factors for rationally manipulating biophysical dynamics, and should also find use in controlling other classes of noisy complex networks.
ISSN:2160-3308
2160-3308
DOI:10.1103/PhysRevX.5.031036