03/12/2021 | News release | Distributed by Public on 03/12/2021 05:47
Categoria: Seminari e Convegni
I will talk about stochastic modeling and approximations of chemical reaction networks. Stochastic effects may play an important role in biological and chemical processes when the system involves the low copy number of some species. A representative stochastic model for a chemical reaction network is using a continuous-time Markov jump process. Since chemical reaction networks are large and nonlinear, it is hard to obtain a closed-form solution for the statistics of interest. In this talk, I will introduce multiscale approximation methods that help reduce network complexity using various scales in species numbers and reaction rate constants. A limiting model with a simpler structure is derived in each time scale of interest, which is used to approximate the behavior of the full model during a specific time interval. Then, the asymptotic behavior of the error between the full model and the limiting model is approximated. I will show the application of the multiscale approximation methods to several examples.