Effective Time-Stepping For The Tau-Leaping Method for Stochastic Simulation Of Well-Stirred Biochemical Networks

Biological processes at the cellular level are noisy. The noise arises due to random molecular collisions, and may be substantial in systems with low molecular counts in some species. This thesis introduces a variable tau-leaping method for the simulation of stochastic discrete mathematical models of well-stirred biochemical systems which is theoretically justified. Numerical tests on several models of biochemical systems of practical interest illustrate the advantages of the adaptive tau-leap method over the existing schemes.