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Computational
Genomics
BME 230, Winter 2008

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Course Information

Location: In E2-599 , Tues/Thurs: 10-11:45am

Information and Handouts

·        Office Hours

·        Schedule of lectures

·        Programming assignments & Problem Sets

·        Frequently Asked Questions

Course Description & Objectives

Analysis of high-throughput genomics datasets using UCSC programming libraries and databases; statistical methods to discover common motifs in biosequences; multiple alignment and search using motif models; constructing phylogenetic trees; hidden Markov models for finding genes, etc.; generative and discriminative methods for analysis of bioinformatics data, support vector machines; locating genes and predicting gene function, comparative genomics; implications of human genome variation and disease association studies using SNPs; and modeling DNA and RNA structures. A substantial project is required.

Prerequisites

BME 100

Grading

Grades are based 80% on 5 homework assignments, 20% on an independent research project. The homework assignments consist of 2 programming projects (50%) and 3 written assignments (30%). Research project grades are based on a written abstract (1%), a ~10 page writeup of the methods and results (15%), and a 10 minute oral presentation (4%). Late policy: Each student can use a total of 7 late days on all assignments. A maximum of 3 late days can be used on any one assignment. No late days can be used for the final research project.

 

Working in Groups

You may work with a partner on programming assignments (not on written assignments).  Please include, with your name, the name of your teammate on all documents that you turn in. (Note: If you do not have much programming experience, it is wise to team up with someone that does!).

 

Communication

We strongly encourage students to come to office hours.

Please do not e-mail the instructors with grading questions. If you want us to explain why we took points off, you can talk to us after class or during office hours. If you want a re-grade, please write an explanation and hand the homework and the explanation to one of the instructors during office hours or after class.

 

Textbook Information

There is one required textbook for the course:

Beginning Perl for Bioinformatics "Biological Sequence Analysis : Probabilistic Models of Proteins and Nucleic Acids” by Durbin, Eddy, Krogh, and Mitchison. REQUIRED

There is one optional textbook for the course:

Beginning Perl for Bioinformatics "Computational Genome Analysis: An Introduction by Deonier, Tavare, Waterman, OPTIONAL

 

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