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An Efficient Tau-Leaping Simulation Method for Stochastic Biochemical Kinetics

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thesis
posted on 22.05.2021, 15:49 by Serguei Rousskikh
Stochastic modeling and simulation of biochemical systems are topics of high interest in Computational Biology. Stochastic mathematical models are critical in accurately capturing the variability observed experimentally in cellular processes, in particular when some species have low molecular numbers. Many, realistic biochemical networks exhibit stiffness, due to the presence of multiple time-scales. For such networks explicit simulation methods are computationally quite intensive. In this thesis, we introduce an improved implicit tau-leaping strategy for the simulation of stochastic biochemical kinetic models. Numerical tests on various biochemical systems of interest in applications show the efficiency of our method.

History

Language

eng

Degree

Master of Science

Program

Applied Mathematics

Granting Institution

Ryerson University Silvana Ilie

LAC Thesis Type

Thesis