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....
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.
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