BIO 5495/BME 537/CSE 587A
Computational Molecular Biology, aka
Algorithms for Computational Biology
Fall 2009
News and announcements
- Unsure where to go: check the directions.
- A copy of the deGroot book, Probability and Statistics, is on reserve at the Becker (medical campus) library.
Overview
This course is a survey of algorithms and methods in biological sequence analysis, with a strong emphasis on probabilistic methods, and systems biology. Sequence analysis topics include introduction to probability, hidden Markov models, gene prediction, sequence alignment, and identification of transcription-factor binding sites. Systems biology topics include discovery of gene regulatory networks, quantitative modeling of gene regulatory networks using ODEs, and quantitative modeling of metabolism using flux balance models.
Our teaching philosphy is shifting from lecture-based to active learning. This means you will be expected to learn the basic material outside of class, through reading and working problems. In class we will emphasize discussion and working on problems and projects. Passive observers never learn much, but in this enviornment it will be more obvious. If you are registered for the course, active participation in class is an absolute requirement. My motto is, "I'm your personal trainer, not your hair dresser."