Appears in collection : Probabilistic techniques for random and time-varying dynamical systems / Méthodes probabilistes pour les systèmes dynamiques aléatoires et variant avec le temps

We consider stochastic models of scalable biological reaction networks in the form of continuous time pure jump Markov processes. The study of the mean field behavior of such Markov processes is a classical topic, with fundamental results going back to Kurtz, Athreya, Ney, Pemantle, etc. However, there are still questions that are not completely settled even in the case of linear reaction rates. We study two such questions. First is to characterize all possible rescaled limits for linear reaction networks. We show that there are three possibilities: a deterministic limit point, a random limit point and a random limit torus. Second is to study the mean field behavior upon the depletion of one of the materials. This is a joint work with Lai-Sang Young.