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Course Announcement - Spring 2006

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Math 127: Mathematics for Computational Biology

**Office hours:**
Wednesdays 8:30-11:00am and by appointment

**Contact:** bernd at math, 925 Evans, 642 4687

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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.
**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....

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