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Accurate Stochastic Simulation Methods for Homogeneous Biochemical Networks

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thesis
posted on 23.05.2021, 18:15 by Farida Ansari
Stochastic models of intracellular processes are subject of intense research today. For homogeneous systems, these models are based on the Chemical Master Equation, which is a discrete stochastic model. The Chemical Master Equation is often solved numerically using Gillespie’s exact stochastic simulation algorithm. This thesis studies the performance of another exact stochastic simulation strategy, which is based on the Random Time Change representation, and is more efficient for sensitivity analysis, compared to Gillespie’s algorithm. This method is tested on several models of biological interest, including an epidermal growth factor receptor model.

History

Language

eng

Degree

Master of Applied Science

Program

Applied Mathematics

Granting Institution

Ryerson University

LAC Thesis Type

Thesis

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