Numerik IV: Stochastic Dynamics in Computational Biology
Stefanie Winkelmann
Comments
Content: This lecture explores mathematical modeling and numerical methods for the description and analysis of biochemical reaction systems. Stochastic dynamics are introduced in the form of continuous-time Markov processes and chemical master equations. Simulation techniques as well as approximation approaches based on stochastic differential equations (SDEs) and ordinary differential equations (ODEs) are discussed. The course emphasizes the interplay between stochastic modeling, numerical analysis, and applications in computational biology.
Target audience:
This course is intended for Master’s students in Mathematics, Informatics and Computational Sciences. It is particularly suitable for students with an interest in numerical analysis, stochastic modeling, and applications in the life sciences. The topics covered in this lecture provide a foundation for current research in computational biology and may serve as a starting point for Master’s thesis projects in this area.
Prerequisites:
Basic knowledge of numerical methods for ordinary differential equations and introductory stochastics.
Suggested reading
S. Winkelmann, C. Schütte: Stochastic Dynamics in Computational Biology. Springer, 2020.
R. Erban, S. J. Chapman: Stochastic Modelling of Reaction–Diffusion Processes. Cambridge University Press, 2020.
N. G. van Kampen: Stochastic Processes in Physics and Chemistry. Elsevier, 1992.
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13 Class schedule
Regular appointments