2024/09/09 by Chuang Xu, Xu, Chuang
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #60J27 #97C42 #FOS: Biological sciences #FOS: Mathematics #Gene Regulatory Network Analysis #Mathematical Biology Tumor Growth #Molecular Networks (q-bio.MN) #Probability (math.PR) #Quantum Mechanics and Applications
paper · pdf · doi:10.48550/arxiv.2409.05340
openalex publication_date 2024/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Reaction networks have been widely used as generic models in diverse areas of applied sciences, such as biology, chemistry, ecology, epidemiology, and computer science. A reaction network incorporating noisy effects is modeled as a continuous time Markov chain (CTMC) and is called a stochastic reaction system. In contrast, the mean field limit of a sequence of volume-scaled stochastic reaction systems as the volume tends to infinity is modeled as an ordinary differential equation (ODE) and is called a deterministic reaction system. Non-explosivity of CTMCs and global existence of solutions of ODEs capture the regularity of respective dynamical processes. In this paper, we study the regularity of reaction systems, in both stochastic and deterministic senses. By constructing a simple linear Lyapunov function, we obtain the regularity in both sense for a class of reaction systems in terms of a simple checkable condition. As an application, we prove that (i) every second-order endotactic mass-action system is regular, and hence (ii) every bimolecular weakly reversible mass-action system is regular. We apply our results to diverse models in biochemistry, epidemiology, ecology, synthetic biology, and natural computing in the literature.