Approximate Bayesian computation for estimating rate constants in biochemical reaction systems

Abstract

To study the dynamic properties of complex biological systems, mathematical modeling has been used widely in systems biology. Apart from the well-established knowledge for modeling techniques, there are still some difficulties while understanding the dynamics in system biology. One of the major challenges is how to infer unknown parameters in mathematical models based on the experimentally observed data sets. This is extremely difficult when the experimental data are sparse and the biological systems are stochastic. To tackle this problem, in this work we revised one computation method for inference called approximate Bayesian computation (ABC) and conducted extensive computing tests to exam..