Modeling the Living Cell

Models and Algorithms in Biology

Spring 2020, AS.250.302


Prof. Margaret Johnson

TAs: Asim Dhungana and Timothy Bedard

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 (python, 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 (sophomore-senior) 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 & H. Garcia