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Coupled Reaction Networks for Noise Suppression

Xiao, Fangzhou and Fang, Meichen and Yan, Jiawei and Doyle, John C. (2019) Coupled Reaction Networks for Noise Suppression. In: 2019 American Control Conference (ACC). IEEE , Piscataway, NJ, pp. 1547-1554. ISBN 978-1-5386-7926-5.

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Noise is intrinsic to many important regulatory processes in living cells, and often forms obstacles to be overcome for reliable biological functions. However, due to stochastic birth and death events of all components in biomolecular systems, suppression of noise of one component by another is fundamentally hard and costly. Quantitatively, a widely-cited severe lower bound on noise suppression in biomolecular systems was established by Lestas et. al. in 2010, assuming that the plant and the controller have separate birth and death reactions. This makes the precision observed in several biological phenomena, e.g., cell fate decision making and cell cycle time ordering, seem impossible. We demonstrate that coupling, a mechanism widely observed in biology, could suppress noise lower than the bound of Lestas et. al. with moderate energy cost. Furthermore, we systematically investigate the coupling mechanism in all two-node reaction networks, showing that negative feedback suppresses noise better than incoherent feedforward achitectures, coupled systems have less noise than their decoupled version for a large class of networks, and coupling has its own fundamental limitations in noise suppression. Results in this work have implications for noise suppression in biological control and provide insight for a new efficient mechanism of noise suppression in biology.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Xiao, Fangzhou0000-0002-5001-5644
Doyle, John C.0000-0002-1828-2486
Additional Information:© 2019 AACC. The authors would like to thank Noah Olsman for constructive discussions. F. X., J. Y. and J. C. D. are partially funded by the Defense Advanced Research Projects Agency (Agreement HR0011-16-2-0049). J. Y. acknowledges the support of NSF/Simons Foundation. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-16-2-0049
Simons FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20181030-075417310
Persistent URL:
Official Citation:F. Xiao, M. Fang, J. Yan and J. C. Doyle, "Coupled Reaction Networks for Noise Suppression," 2019 American Control Conference (ACC), Philadelphia, PA, USA, 2019, pp. 1547-1554. URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90486
Deposited By: Tony Diaz
Deposited On:30 Oct 2018 17:12
Last Modified:16 Nov 2021 03:33

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