Individual Molecules Dynamics in Reaction Network Models

DOI10.1137/21m1459563zbMath1519.92072arXiv2111.08559OpenAlexW4382061637MaRDI QIDQ6171202

Daniele Cappelletti, Grzegorz A. Rempała

Publication date: 17 July 2023

Published in: SIAM Journal on Applied Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2111.08559

zbMATH Keywords

stochastic approximationlaw of large numbersSkorokhod topologymathematical epidemiologydynamical survival analysisPoisson process representationsingle-molecule dynamics

Mathematics Subject Classification ID

Epidemiology (92D30) Biochemistry, molecular biology (92C40) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Systems biology, networks (92C42)

Cites Work

• Unnamed Item
• Unnamed Item
• Error analysis of tau-leap simulation methods
• Large deviations theory for Markov jump models of chemical reaction networks
• Large deviations for Markov jump processes with uniformly diminishing rates
• Tier structure of strongly endotactic reaction networks
• Central limit theorems and diffusion approximations for multiscale Markov chain models
• A countable representation of the Fleming-Viot measure-valued diffusion
• Projecting COVID-19 cases and hospital burden in Ohio
• Markov Chains
• Structure and stability of certain chemical networks and applications to the kinetic proofreading model of T-cell receptor signal transduction
• On Constrained Langevin Equations and (Bio)Chemical Reaction Networks
• Throwing stones and collecting bones: Looking for Poisson‐like random measures
• Stochastic Analysis of Biochemical Systems
• Strong Gaussian approximation of metastable density-dependent Markov chains on large time scales

This page was built for publication: Individual Molecules Dynamics in Reaction Network Models