640:338 Discrete and Probabilistic Models
Home Page, Spring 2006
TTH6 (5:00-6:20), SEC, Room 218
The text is available (free!) on-line at
Daniel Ocone, email@example.com
Office Hours: Hill 518:
Tuesday and Thursday, 3:15-4:45 (before class); Wednesday, 10:30-11:30;
or by appointment.
Lecture schedule, problem sets
and reading assignments, etc.
Syllabus by topic
Tests, homework, grades:
There will be weekly, graded problem sets, two midterms, and a final.
The final grade will be computed from an average of
the final grade (200 points), the midterm grades (100 points each),
and the homework grades (100 points).
The midterms are
tentatively scheduled for Feb. 21 and March 30.
THE SPRING 2006 semester
will focus on probabilistic and
dynamic programming methods in the analysis of
biological sequences and in genetics.
The course introduces models from population biology
for the study of
the evolution of gene frequency, models from genomics
for the statistical description and for the evolution
of genomes and proteomes, and the mathematical tools
for their analysis.
Here is a summary:
- Basic populations genetics
as an introduction to probabilistic models in biology.
- Continuous random variables. Independent, identically distributed
random sequences, geometric, exponential, and normal random variables,
and Poisson processes. Application to coverage analysis in DNA
- Likelihood functions, Maximum Likelihood Estimation,
hypothesis testing, and application
to models for biological sequences.
- Dynamic Programming and sequence alignment.
- Markov chain basics and Hidden Markov models for
sequence evolution and applications to alignment.