Likelihood-free parameter inference

Biochemical reaction networks represent complex cellular regulatory mechanisms. These networks are typically analyzed using discrete stochastic simulation models. The models may involve numerous reactions involving a large number of chemical species, governed by highly uncertain parameters. Given existing data pertaining to a biochemical reaction network, one is often interested in inferring the values of the […]