The Annals of Applied Probability
- Ann. Appl. Probab.
- Volume 23, Number 2 (2013), 529-583.
Separation of time-scales and model reduction for stochastic reaction networks
A stochastic model for a chemical reaction network is embedded in a one-parameter family of models with species numbers and rate constants scaled by powers of the parameter. A systematic approach is developed for determining appropriate choices of the exponents that can be applied to large complex networks. When the scaling implies subnetworks have different time-scales, the subnetworks can be approximated separately, providing insight into the behavior of the full network through the analysis of these lower-dimensional approximations.
Ann. Appl. Probab., Volume 23, Number 2 (2013), 529-583.
First available in Project Euclid: 12 February 2013
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 60J27: Continuous-time Markov processes on discrete state spaces 60J80: Branching processes (Galton-Watson, birth-and-death, etc.) 60F17: Functional limit theorems; invariance principles 92C45: Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) [See also 80A30] 80A30: Chemical kinetics [See also 76V05, 92C45, 92E20]
Kang, Hye-Won; Kurtz, Thomas G. Separation of time-scales and model reduction for stochastic reaction networks. Ann. Appl. Probab. 23 (2013), no. 2, 529--583. doi:10.1214/12-AAP841. https://projecteuclid.org/euclid.aoap/1360682022