Department of Mathematics

Van Vleck Hall, 480 Lincoln Drive, Madison, WI

Math 605: Stochastic Methods for Biology

Background and Goals: 

This course is, first and foremost, an introduction to stochastic processes (models that incorporate randomness) that is equivalent in level, and to a large extent content, to Math 632.  However, the applications will be drawn primarily from the biosciences, with a special emphasis on the continuous time Markov chains used to model biochemical and other population processes.  Further, as simulation is a large part of how scientists study their models, we will spend considerable time on these methods (such as the well known ``Gillespie Algorithm'').  Matlab will be the software package of choice for the course and each homework assignment will incorporate at least one Matlab exercise. 


Math 632

Subsequent Courses: 

Math 635, 735, 831-832

Course Content: 
  1. Discrete Time Markov Chains.
  2. Branching processes.
  3. Continuous time Markov Chains.
  4. Diffusion processes.
  5. Applications to biology, especially the continuous time Markov chains used to model biochemical reaction networks.
  6. Computational/Simulation methods.


Math/Stat 431; Math/Stat 309 or Stat 311; or cons inst. Basic knowledge pertaining to linear algebra and linear differential equations.

UW-Madison Department of Mathematics
Van Vleck Hall
480 Lincoln Drive
Madison, Wi  53706

(608) 263-3054

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