Models and Algorithms in Biophysics
Spring 2018, AS.250.302
Prof. Margaret Johnson
TA: Melissa Mai and Ruchita Kothari
Summary: Introduction to physics-based and mathematical modeling approaches used to represent biological systems including molecular and cellular systems and multi-cellular or fluidic systems.
Students will learn algorithms for implementing models computationally and perform implementations in MATLAB (c/c++ also allowed). We will discuss types of approximations made to develop useful models of complex biological systems, their foundations in statistical mechanics, theory, or empirical observations, and comparisons of model predictions with experiment.
The course contains 5 major sections:
1) Thermodynamics and basic statistical mechanics
2) Dynamics of equilibrium and non-equilibrium systems, equations of motion
3) Parameter estimation, dimensionality reduction for model fitting and data analysis
4) Fluid Dynamics and continuum models
5) Additional topics: Membranes, Cytoskeletal assembly, Networks, Action potentials, Gene expression
Appropriate for: Undergraduate and graduate students with some programming experience (at least an intro programming course) interested in learning modeling and simulation approaches used in biology.
Lecture: Tues & Thurs 1:30-2:45pm Jenkins Hall Rm 107
Lab: Mon 5-6pm Jenkins Hall Rm 122
Required Textbook: Physical Biology of the Cell R. Phillips, J. Kondev, J. Theriot