Results on stochastic reaction networks with non-mass action kinetics

Math Biosci Eng. 2019 Mar 12;16(4):2118-2140. doi: 10.3934/mbe.2019103.

Abstract

In 2010, Anderson, Craciun, and Kurtz showed that if a deterministically modeled reaction network is complex balanced, then the associated stochastic model admits a stationary distribution that is a product of Poissons [1]. That work spurred a number of followup analyses. In 2015, Anderson, Craciun, Gopalkrishnan, and Wiuf considered a particular scaling limit of the stationary distribution detailed in [1], and proved it is a well known Lyapunov function [2]. In 2016, Cappelletti and Wiuf showed the converse of the main result in [1]: if a reaction network with stochastic mass action kinetics admits a stationary distribution that is a product of Poissons, then the deterministic model is complex balanced [3]. In 2017, Anderson, Koyama, Cappelletti, and Kurtz showed that the mass action models considered in [1] are non-explosive (so the stationary distribution characterizes the limiting behavior). In this paper, we generalize each of the three followup results detailed above to the case when the stochastic model has a particular form of non-mass action kinetics.

Keywords: Lyapunnov functions; continuous-time Markov chains; explosivity; non-mass action kinetics; reaction networks; stationary distribution.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Kinetics
  • Markov Chains
  • Models, Biological
  • Physics / methods*
  • Poisson Distribution
  • Software
  • Stochastic Processes*