CSE 427,  Au '18:  Computational Biology

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Administrative  FAQ  Schedule & Reading Course Email/BBoard  Class List Archive  Google Groups Lecture Notes  1:  Intro  2:  Alignment & Scoring    Needleman-Wunsch Ex (.xlsx)    Smith-Waterman Ex (.xlsx)  3:  BLAST & More Scoring    Bio Notes - PCR & Seq  4:  MLE & EM    EM Example (.xls)  5:  Motifs  6:  Markov Models    HMM Example (.xls)    Reading (.pdf)  7:  Genes  8:  Noncoding RNA    Bio Notes - Replication    Bio Notes - PCR & Seq  9:  CMs: ncRNA Models  10:  Diatoms  11:  Wrapup Lecture Recordings  Here Resources  Pubmed  BLAST  PDB  NHGRI Talking Glossary  ORNL Genome Glossary  A Molecular Biology Glossary

Lecture:  EEB 045 (room info) TuTh 1130- 1250    Office Hours Location Phone Instructor:  Larry Ruzzo, ruzzocs  Tu 3:30- 4:30  CSE 554  (206) 543-6298 TA :  Sean Jaffee, sjaffe1cs  M 2:00- 3:00  5th floor breakout  TA :  Daniel Jones, dcjonescs  Th 1:00- 2:00  CSE 220  Course Email: cse427a_au18@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.  Discussion Board: Also feel free to use the course-specific Google Group to discuss homework, etc. 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 "free 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 25% per day for late homework in excess of the free days. Weekends count as one day; e.g. due Friday, submitted Sunday = 1 day late, Monday = 2 days late. Textbooks: None. 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: © 1993-2018, the Authors and the Department of Computer Science and Engineering, University of Washington.

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