Course Announcement - Spring 2006

Math 127: Mathematics for Computational Biology

Instructor: Bernd Sturmfels

Office hours: Wednesdays 8:30-11:00am and by appointment
Contact: bernd at math, 925 Evans, 642 4687

Time and Place: Tuesdays and Thursdays, 12:30-2:00pm, 81 Evans Hall

Prerequisites: Some basics of Discrete Mathematics, Statistics and Abstract Algebra. An interest in Molecular Biology is welcome but not necessary. A crucial prerequisite is willingness to work very hard and to interact with other students, who will have different backgrounds from your own. If you are unsure whether this course is suitable for you, please take a look at the course text, and then ask the instructor. In the past this course was taught by Lior Pachter, so you can also ask Lior.

Course text: Algebraic Statistics for Computational Biology,
edited by Lior Pachter and Bernd Sturmfels, Cambridge University Press, 2005.

Syllabus: This course is an introduction to mathematical foundations which we believe are relevant for biological sequence analysis. The emphasis lies on algebraic statistics (e.g. hidden Markov models) and discrete algorithms (e.g. neighbor-joining for tree construction). We will have an occasional guest speaker discussing biological applications (e.g. comparative genomics). Such a guest lecture may be given by one of our two....

Consultants: Niko Beerenwinkel and Nick Eriksson.

This class does not have a teaching assistent but the two experts listed above kindly agreed to act as ''consultants''.
Niko and Nick will be available for your questions, and they will help by mentoring some of the course projects.
The lecture given by Niko on Thursday, February 2, is here here in pdf format.
The lecture on Grobner bases given on Tuesday, April 4, is here here in ppt format.

Homework: There will be a biweekly homework sheet during the first half of the course.

Course projects: On February 7, we shall form research teams. By the second week of March, the homework will stop, so everyone can concentrate on their project. Each team will be given an opportunity to present their results towards the end of the semester.

Participants: I anticipate a mix of undergraduate students and graduate students, both from mathematics and from other departments, in this class. Participants will greatly benefit from working with other members of this diverse group.

Grading: Your background will be taken into consideration when assigning the final grades, which I expect to end up very good for most participants. The course grade will be based on the homework and the projects, with a bias towards the latter.

Further Reading:
D. Gusfield: Algorithms on Strings, Trees, and Sequences, Cambridge University Press, 1997
R. Durbin, S. Eddy, A. Korgh and G. Mitchison: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, 1998