Model reduction for stochastic chemical systems with abundant species
Stephen Smith, Claudia Cianci, Ramon Grima

TL;DR
This paper develops a hybrid stochastic model for biochemical systems with abundant and scarce species, simplifying analysis and providing exact solutions for certain networks, thus advancing understanding of molecular fluctuations.
Contribution
It introduces a hybrid stochastic framework that reduces complexity by focusing on non-abundant species and proves its accuracy and exact solvability for specific biochemical networks.
Findings
Hybrid model accurately describes non-abundant species fluctuations.
Exact solutions obtained for gene expression and enzyme catalysis networks.
Hybrid and conventional models agree for certain classes regardless of molecule number separation.
Abstract
Biochemical processes typically involve many chemical species, some in abundance and some in low molecule numbers. Here we first identify the rate constant limits under which the concentrations of a given set of species will tend to infinity (the abundant species) while the concentrations of all other species remains constant (the non-abundant species). Subsequently we prove that in this limit, the fluctuations in the molecule numbers of non-abundant species are accurately described by a hybrid stochastic description consisting of a chemical master equation coupled to deterministic rate equations. This is a reduced description when compared to the conventional chemical master equation which describes the fluctuations in both abundant and non-abundant species. We show that the reduced master equation can be solved exactly for a number of biochemical networks involving gene expression and…
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