Network Conditions for Positive Recurrence of Stochastically Modeled Reaction Networks and Mixing

Jinsu Kim
University of Wisconsin – Madison
PhD Graduate Student

“Reaction networks are graphical configurations that can be used to describe biological interaction networks. If the abundances of the constituent species of the system are low, we can model the dynamics of species counts in a jump by jump fashion as a continuous-time Markov chain. In this talk, we will mainly focus on which underlying structure of the networks imply positive recurrence for the associated continuous-time Markov chain. I will also present results related to their mixing times, which give the time required for the distribution of the continuous-time Markov chain to get close to the stationary distribution”.

View Kim’s Seminar Flyer