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CSE 427, Au '21: Computational Biology |
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Course Email: cse427a_au21@uw.edu. Staff announcements and general interest student/staff Q&A about homework, lectures, etc. The instructor and TAs are subscribed to this list. Enrolled students are as well, but probably should change their default subscription options. Messages are automatically archived. For fastest response, questions not of general interest should be directed to the instructor and TAs collectively via the "course staff" link at left. Individual email addresses (above) may also be used, if needed. Discussion Board: Also feel free to use the course-specific Ed Discussion Board to discuss lectures, homework, and anything else (loosely) course-related. 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. Prerequisites: CSE 312; CSE 332 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%. Late Policy: We allow 5 "late days" in total over the quarter without penalty; e.g., one assignment may be 5 days late, or one assignment may be 2 days late and another may be 3 days late. We will deduct 20% per day for late homework in excess of the 5 allowed late days. Textbooks: Richard Durbin, Sean R. Eddy, Anders Krogh and Graeme Mitchison, Biological Sequence Analysis: Probabilistic models of proteins and nucleic acids, Cambridge, 1998. Errata. (Available from Amazon, etc.) Also, the e-book is available for free with a uw.edu netid here. 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: © 1993-2021, the Authors and the Department of Computer Science and Engineering, University of Washington. |
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Computer Science & Engineering University of Washington Box 352350 Seattle, WA 98195-2350 (206) 543-1695 voice, (206) 543-2969 FAX |
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