Multiscale Analysis of Reaction Networks
L. Sbano, M. Kirkilionis

TL;DR
This paper develops a multiscale stochastic framework for analyzing biochemical reaction networks, bridging microscopic molecular interactions and macroscopic concentration dynamics through asymptotic analysis.
Contribution
It introduces a novel multiscale stochastic modeling approach for biochemical networks, deriving effective macroscopic equations from microscopic processes.
Findings
Derived Fokker-Planck type equations for reaction networks.
Demonstrated the separation of time scales between concentration changes and conformational dynamics.
Provided a systematic asymptotic method for coarse-graining stochastic reaction models.
Abstract
In most natural sciences there is currently the insight that it is necessary to bridge gaps between different processes which can be observed on different scales. This is especially true in the field of chemical reactions where the abilities to form bonds between different types of atoms and molecules create much of the properties we experience in our everyday life, especially in all biological activity. There are essentially two types of processes related to biochemical reaction networks, the interactions among molecules and interactions involving their conformational changes, so in a sense, their internal state. The first type of processes can be conveniently approximated by the so-called mass-action kinetics, but this is not necessarily so for the second kind where molecular states do not define any kind of density or concentration. In this paper we demonstrate the necessity to study…
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Taxonomy
Topicsstochastic dynamics and bifurcation · Gene Regulatory Network Analysis · Advanced Thermodynamics and Statistical Mechanics
