CSE 427,  Wi '08:  Computational Biology

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Administrative  Syllabus  Schedule & Reading Course Email  Class List Archive  E-mail Course Staff Assignments  HW #1  HW #2  HW #3  HW #4 Lecture Slides  1: Intro & Bio Basics (1-up, 4-up)  2: Gene Finding (1-up, 4-up)  3: MMs & HMMs (1-up, 4-up)  4: Alignment; DNA Replication (1-up, 4-up)  5: BLAST, Scoring; Sequencing (1-up, 4-up)  6: Multiple Sequence Alignment (1-up, 4-up)  7: Gene Regulation (1-up, 4-up)  8: RNA Folding; RNA Function (1-up, 4-up)  9: RNA Motifs, Discovery, & Search (1-up, 4-up) Previous Versions of 427  CSE 490c, 2006  CSE 490c, 2007 Resources  Pubmed  BLAST  PDB  NCBI Science Primer  NHGRI Talking Glossary  ORNL Genome Glossary  A Molecular Biology Glossary

Lecture:  Mor 234 (schematic) TuTh 12:00- 1:20    Office Hours Phone Instructor:  Larry Ruzzo, ruzzo at cs  TBA CSE 554  (206) 543-6298 TA:  Zizhen Yao, yzizhen at cs  TBA Course Email: cse427a_wi08@u.washington.edu. Use this list to ask and/or answer questions about homework, lectures, etc. The instructor and TA are subscribed to this list. All messages are automatically archived.  Questions not of general interest may be directed to the instructor: ruzzo at cs. You can (and perhaps should) change your subscription options. Catalog Description: Algorithmic and analytic techniques underlying analysis of large-scale biological data sets such as DNA, RNA, and protein sequences or structures, expression and proteomic profiling. Hands-on experience with databases, analysis tools, and genome markers. Applications such as sequence alignment, BLAST, phylogenetics, and Markov models. Prerequisite: CSE 326 Credits: 3 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, possibly including a small project: 90%; class participation: 10%. Textbook: None. References: See Schedule & Reading Portions of the CSE 427 Web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly credited. The CSE 427 Web: © 1993-2008, Department of Computer Science and Engineering, University of Washington.

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