MATH 428/528: Stochastic Elements in Mathematical Biology

Spring 2021



Instructor: Yevgeniy Kovchegov
e-mail: kovchegy @math. oregonstate.edu
Office: Kidder 60
Office Phone No: 7-1379
Office Hours: by appointment, via Zoom



Instructions: MWF 1:00pm to 1:50pm, via Zoom.

Course description: This course is an introduction to stochastic modeling of biological processes. Stochastic models covered may include Markov processes in both continuous and discrete time, urn models, branching processes, and coalescent processes. Biological applications modeled may include genetic drift, population dynamics, genealogy, demography, and epidemiology. Mathematical results will be qualitatively interpreted and applied to the biological process under investigation.

The course will cover the following topics:

A variety of mathematical techniques will be covered when analyzing these models.

Syllabus:  PDF



Assignments:



Schedule:
Monday, March 29  Review of probability. Conditional probability. Bayes’ Theorem. Lectures 1-3 slides (PDF)
Wednesday, March 31  Review of probability. Conditional probability. Bayes’ Theorem. Independent events. Lectures 1-3 slides (PDF)
Friday, April 2  Review of probability. Bayes’ Theorem. Independent events. Examples. Lectures 1-3 slides (PDF)
Monday, April 5  Review of combinatorics. Permutations and combinations. Generalized combinations. Binomial theorem. Lecture 4 slides (PDF)
Wednesday, April 7  Introduction to random variables. Binomial random variable. Expectation of a random variable. Wright-Fisher Model. Lecture 5 slides (PDF)
Friday, April 9  Binomial random variable. Expectation of a random variable. Wright-Fisher Model. Poisson random variable. Geometric random variables. Variance and standard deviation. Lecture 6 slides (PDF)
Monday, April 12  Variance and standard deviation of discrete random variables. Markov and Chebyshev inequalities. Lecture 7 slides (PDF)