2007/11/28 by M. J. Morelli, Marco J. Morelli, Rosalind J. Allen +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Chemistry · Mathematics · #Biological system #Biology #Bistability #Chemical reaction #Chemistry #Computer science #DNA #Dissociation (chemistry) #Evolution and Genetic Dynamics #Gene Regulatory Network Analysis #Granularity #Kinetics #Master equation #Mathematics #Microbial Metabolic Engineering and Bioproduction #Physics #Quantum #Quantum mechanics #Rate equation #Set (abstract data type) #Statistical physics #Stochastic process #q-bio.MN #q-bio.QM
paper · pdf · doi:10.1063/1.2821957
46 pages, 5 figures
arxiv created 2007/11/28 · openalex publication_date 2008/01/28 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In many stochastic simulations of biochemical reaction networks, it is desirable to "coarse grain" the reaction set, removing fast reactions while retaining the correct system dynamics. Various coarse-graining methods have been proposed, but it remains unclear which methods are reliable and which reactions can safely be eliminated. We address these issues for a model gene regulatory network that is particularly sensitive to dynamical fluctuations: a bistable genetic switch. We remove protein-DNA and/or protein-protein association-dissociation reactions from the reaction set using various coarse-graining strategies. We determine the effects on the steady-state probability distribution function and on the rate of fluctuation-driven switch flipping transitions. We find that protein-protein interactions may be safely eliminated from the reaction set, but protein-DNA interactions may not. We also find that it is important to use the chemical master equation rather than macroscopic rate equations to compute effective propensity functions for the coarse-grained reactions.