CSC2417: Algorithms for Genome Sequence Analysis

Winter 2009

Lectures: W 10-12 in Bahen 2139

Instructor: Michael Brudno
Office: Pratt (PT) 286C
Office Hours: Fri 10-11 and by appointment


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  • First class will be Jan 07

    General information

    This 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 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.

    The basic requirements for the class will be a course project (40% of the grade), three homework assignments (45% total), and reading/class participation (15%).

    Administrative details:
    The class will satisfy the 2c breadth.