Elimination of intermediate species in multiscale stochastic reaction networks

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

We study networks of biochemical reactions modelled by continuoustime 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.

OriginalsprogEngelsk
TidsskriftAnnals of Applied Probability
Vol/bind26
Udgave nummer5
Sider (fra-til)2915-2958
Antal sider44
ISSN1050-5164
DOI
StatusUdgivet - 1 okt. 2016

ID: 170349667