BCB 410 & CSC2417: Algorithms for Genome Sequence Analysis

Fall 2010


Lectures: M 10-12 in Bahen 2179

Instructor: Michael Brudno
Office: Pratt (PT) 286C
Office Hours: TBA and by appointment

Announcements

General information

Overview:
This joint undergraduate/graduate course will cover some exciting algorithms that have been developed to analyze genomic and functional data, including Genome comparison and assembly, gene prediction, localization of regulatory elements in the genome, and analysis and comparison of biological networks. While the emphasis of the class will be on discrete algorithms, we occasionally will talk about probabilistic models (such as HMMs), and the interplay between discrete and probabilistic models. The course is intended for both undergraduate student's from the Bioinformatics and Computational Biology program and computer science graduate students, and all of the required biology will be explained in the class. Students in biological and related sciences with a strong computational background are encouraged to participate.

Expected Background:
Students should be familiar with algorithms (at least CSC 373 level), basic probability theory.

Grading:
The basic requirements for the class will be a course project (45% of the grade for CSC 2417 students, 30% for BCB 410), three homework assignments (45% for CSC 2417 and 60% for BCB 410), and class participation (10%).

Students in BCB 410 have the option of using the 2417 grading scheme (i.e. reweighing the project to be a larger fraction of the grade), but not vice-versa. The project can be on any topic (loosely) related to computational biology.

Administrative details:
For CS MSc students this class is in breadth category 4 (Human Centric and Interdisciplinary computing).