ELIMINATION OF INTERMEDIATE SPECIES IN MULTISCALE STOCHASTIC REACTION NETWORKS

成果类型:
Article
署名作者:
Cappelletti, Daniele; Wiuf, Carsten
署名单位:
University of Copenhagen
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
DOI:
10.1214/15-AAP1166
发表日期:
2016
页码:
2915-2958
关键词:
chemical-reaction networks mass-action kinetics approximation SEPARATION accurate
摘要:
We study networks of biochemical reactions modelled by continuous time Markov processes. Such networks typically contain many molecular species and reactions and are hard to study analytically as well as by simulation. Particularly, we are interested in reaction networks with intermediate species such as the substrate-enzyme complex in the Michaelis Menten mechanism. Such species are virtually in all real-world networks, they are typically short-lived, degraded at a fast rate and hard to observe experimentally. We provide conditions under which the Markov process of a multiscale reaction network with intermediate species is approximated by the Markov process of a simpler reduced reaction network without intermediate species. We do so by embedding the Markov processes into a one-parameter family of processes, where reaction rates and species abundances are scaled in the parameter. Further, we show that there are close links between these stochastic models and deterministic ODE models of the same networks.