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Computational
Genomics
BME 230, Winter 2005

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Course Information

Location: Baskin Engineering Rm 156, Tues/Thurs: 4-5:30pm

Information and Handouts

·        Office Hours

·        Schedule of lectures

·        Programming assignments & Problem Sets

·        Frequently Asked Questions

Course Description & Objectives

Genomics databases: analysis of high-throughput genomics datasets; BLAST and related sequence comparison methods; pairwise alignment of biosequences by dynamic programming; statistical methods to discover common motifs in biosequences; multiple alignment and database search using motif models; constructing phylogenetic trees; hidden Markov models for finding genes, etc.; discriminative methods for analysis of bioinformatics data, neural networks, and support vector machines; locating genes and predicting gene function, including introduction to linkage analysis 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 3 written and 2 programming assignments, 20% on a project proposal. Credit will be given for class presentation. 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 project.

 

Working in Groups

Encouraged to work together on programming assignments (not on written assignments) in groups of no more than 2.  Please list the names of your teammates on what you turn in.

 

If you do not have much programming experience, please try to team up with those who do.

 

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 and two optional textbooks for the course:

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

 

"Introduction to Bioinformatics Algorithms" by Jones and Pevzner. OPTIONAL

"Bioinformatics: Sequence and Genome Analysis " by David Mount. OPTIONAL

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