Deciphering noise amplification and reduction in open chemical reaction networks
Fabrizio Pucci, Marianne Rooman

TL;DR
This paper analyzes how noise is amplified or reduced in open chemical reaction networks using stochastic differential equations, revealing that flux direction influences noise levels, with implications for biological and synthetic systems.
Contribution
It provides a theoretical framework linking network deficiency, flux direction, and noise modulation in chemical reaction networks, extending understanding beyond detailed-balanced systems.
Findings
Zero deficiency systems have uncorrelated species with Poisson noise.
Flux direction determines noise amplification or reduction in deficiency one systems.
The relation between flux and noise is generalized to higher deficiency systems.
Abstract
The impact of random fluctuations on the dynamical behavior a complex biological systems is a longstanding issue, whose understanding would shed light on the evolutionary pressure that nature imposes on the intrinsic noise levels and would allow rationally designing synthetic networks with controlled noise. Using the It\=o stochastic differential equation formalism, we performed both analytic and numerical analyses of several model systems containing different molecular species in contact with the environment and interacting with each other through mass-action kinetics. These systems represent for example biomolecular oligomerization processes, complex-breakage reactions, signaling cascades or metabolic networks. For chemical reaction networks with zero deficiency values, which admit a detailed- or complex-balanced steady state, all molecular species are uncorrelated. The number of…
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