CS 88/188: Introduction to Bioinformatics, Spring 2005

Computation is vital for modern molecular biology, helping scientists to model, predict the behaviors of, and control the molecular machinery of the cell. This course will study algorithmic challenges in analyzing biomolecular sequences (what genes encode an organism, and how are genes related across organisms?), structures (what do the proteins constructed for these genes look like, and what does that tell us about their mechanisms?), and functions (what do these things do, and how do they interact with each other in doing it?). The course is application-driven, but focused on the underlying algorithms and information processing techniques, employing approaches from search, optimization, pattern recognition, and so forth.

Here's a fun little flyer for CS types.

This is an introductory course targeted at advanced undergraduate and beginning graduate students in computer science. A background in biology is not required, but students should be interested in catching up quickly on some basic molecular biology and biochemistry. Bruce Donald's Topics in Computational Molecular Biology is a natural successor for those who would like additional depth in the applications and algorithms.

While the course is structured from an algorithmic perspective, I very much welcome and encourage the participation of students from the life sciences, statistics, and other related disciplines. Naturally, a basic understanding of and interest in computational issues is expected. Please contact me to discuss your background and interests.

The goals of this course include both broad exposure to some important algorithmic challenges and approaches in bioinformatics, as well as relatively deeper experience with a few examples. The lectures and readings will provide a fairly general (for a ten-week course) survey of the field. Written homework exercises will help gain familiarity with, and insights into, some of the basic algorithms. A programming component in each of the first three homeworks will give the chance to explore an algorithm and its applications more deeply. Finally, a term project will provide even more focus on a topic of choice.

All students are expect to read, understand, and follow the course policies.

The course schedule lists due dates, topics, and readings.