Parameter estimation for Gillespie algorithm

Abstract

Gillespie algorithm or the stochastic simulation algorithm (SSA) plays an important role in computational biology for simulating systems with stochastic events. This thesis is about improving parameter estimation techniques for the method of Gillespie by increasing its accuracy and computational speed mainly through estimation of reaction rate constants. The research has also shown that this approach can be applied to various biochemical situations. Among them is where the reaction rate constants were successfully optimized, hence they improve the predictive capability of these simulations. Additionally, it provides the understanding of stochastic kinetics which contribute to both theoretical foundations and practical methods used in modeling complex biological systems.