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  CSE P590BSp '11:  Computational Biology (Professional Masters Program)
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Homework
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Lecture Notes
 1:  Introduction; Bio Basics
 2:  Alignment; DNA Replication
 3:  BLAST; Scoring; DNA Sequencing
 4:  MLE & EM
   EM Example (.xls)
 5:  Motifs; Gene Regulation
 6:  HMMs
   HMM Example (.xls)
 7:  Gene Finding; Splicing
 8:  RNA Function & Structure
 9:  RNA Search & Discovery
 10:  ChIPseq & Summary
Previous Versions
 CSEP 590A, 2008
 CSEP 590A, 2006
 CSE 590TV, 2003
Resources
 Pubmed
 NCBI Science Primer
 NHGRI Talking Glossary
 ORNL Genome Glossary
 A Molecular Biology Glossary
 BLAST
 Swiss-Prot
 PDB
   

Lecture:  EEB 037 (schematic) Th 6:30- 9:20PM 
 
Office Hours Location Phone
Instructor:  Larry Ruzzo, ruzzocs  By appt. CSE 554  (206) 543-6298
TA:  Brandon Blakeley, blakeleycs  By appt.

Course Email: csep590b_sp11@uw.edu. Announcements and general interest Q&A about homework, lectures, etc. The instructor and TA are subscribed to this list. Enrolled students are as well, but probably should change their default subscription options. Messages are automatically archived. 

Discussion Board: Also feel free to use Catalyst GoPost to discuss homework, etc.

Catalog Description: An introduction to the use of computational methods for the understanding of biological systems at the molecular level.

Prerequisite: None

Credits: 4

Learning Objectives: The availability of the complete genome sequences of humans and other organisms is one of the landmark achievements of science. Understanding this enormous volume of data is a problem that will challenge scientists for decades to come, and the nature and scope of the problem means that computer scientists will play a vital role. The primary objective of the course is for students to understand the variety of computational problems and solutions that arise in this interdisciplinary field. Students will learn enough of the basic concepts of molecular biology to understand the context for the computational problems presented in the rest of the course. They will learn how some of the computational methods they have encountered in other courses can be applied to solve problems in modern molecular biology. An important component is to learn the nature and capabilities of some of the key public databases available for the solution of these problems, as well as publicly available computational analysis tools and the algorithmic principles underlying them.

Grading: Homework-based (no exams). Homework will include programming, paper & pencil exercises and some online discussion of readings.

Textbook: Richard Durbin, Sean R. Eddy, Anders Krogh and Graeme Mitchison, Biological Sequence Analysis: Probabilistic models of proteins and nucleic acids, Cambridge, 1998.  (Available from U Book Store, Amazon, etc.)  Errata.

References: See Schedule & Reading


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