This course covers the basic concepts of biophysical modeling, It will address topics at the interface of biophysics/chemistry and computer/computational science at an introductory level. No prior programming experience is necessary! The course is structured so that students can learn the needed programming concepts along the way, using Matlab which has many built-in methods to simplify the learning process.

The course is broken up into the following modules:

• Basic numeral differentiation and quadrature methods
• Monte Carlo integration and sampling
• The theory of Brownian motion and Brownian dynamics algorithms
• Lattice based sampling of model spin systems as used in modeling membrane phase behavior
• Techniques of particle simulations, molecular dynamics algorithms
• Network dynamics for modeling chemical and system-level networks of interacting species

Class Format:

This class will be highly interactive with most of the class time spent working on problems both individually and in groups. At the start of the semester, concepts important for each module will be introduced via lecture and time will be dedicated to writing code to implement and explore the module topics. Later in the semester, class time will be entirely dedicated to working on projects, giving progress reports, and presenting final results.