Chemical reaction networks with reaction rates changing stochastically in time
Conference
65th ISI World Statistics Congress 2025
Format: IPS Abstract - WSC 2025
Keywords: markov-chain, microbiology
Session: IPS 709 - Stochastic Processes and Applications
Wednesday 8 October 10:50 a.m. - 12:30 p.m. (Europe/Amsterdam)
Abstract
Stochastic reaction networks are typically used as models in biochemistry. In their classical definition, the rates at which chemical reactions occur only depend on the current state. However this is not true in many biological systems, where the rate values at a given state fluctuate over time. I will present some models where the rates depend on both the current configuration and another stochastic process, which is not directly affected by the system of interest. I will focus on the study the positive recurrence of this more general model under the assumption of "monomolecularity". Here, under certain conditions, the stationary distribution exists and is a mixture of Poisson distributions, uniquely identified as the law of a fixed point of a stochastic recurrence equation. I will further show some results on models with rates that randomly switch between different fixed values.