CSE 527, Au '05: Computational Biology

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Old Lecture Notes  1. Overview  2. Microarray Overview          (source: 04notes02.html)  3. Microarray Case Study  4. Clustering: Basics  5. Clustering: Model-Based          (source: 04notes05.doc)  6. MLE and EM          (source: 04notes06.zip)  7. EM; Weight Matrices  8. ('03 #12) MEME          (source: 03notes12.tex)  9. Gibbs Sampler  10. ('03 #15) Gibbs w/ Gaps          (source: 03notes15.tex)  11. ('03 #16) Phylogenetic Footprinting          (source: 03notes16.doc)  12. ('03 #17) Hidden Markov Models, I          (source: 03notes17.zip)  13. ('03 #18) Hidden Markov Models, II          (source: 03notes18.zip)  14. ('03 #19) Pfam; Gene Finding          (source: 03notes19.tex)  15. Gene Finding; Splicing          (source: 04notes15.tex)  16. Splicing          (source: 04notes16.doc)  17. RNA Secondary Structure          (source: 04notes17.zip)  18. Covariance Models          (source: 04notes18.zip)  19. Covariance Models & Rfam          (source: 04notes19.doc)

Note Taking: One of the course requirements is that each student act as ``scribe'' for one lecture. Your job is to produce a legible set of notes for that lecture that I can put on the web for the benefit of the rest of the class. My slides will also be available on the web, so there's no need to reproduce those, but you can give more background on the problems being addressed, the methods covered, fill in details I talked about in class that aren't on the slides, summarize in-class discussion, add extra figures or pictures, add references, suggest exercises or further reading, etc. Basically anything that might help people learn the material. At left are links to previous year's notes. I don't cover all the same material, but to the extent that I do, you may use thse notes as a starting point, and refine them. Links to the "source" files are given, as well as PDF's; feel free to down load and edit them. (If you do, leave the original author's names on it, but add your own.) If the original was more than one file (e.g. a text file plus a figure or two) then they are bundled together as a single .zip file; let me know if you have trouble unpacking them. Notes are mostly done in LaTeX or Word, but I don't care too much -- html is fine, plain text is fine, one of the old ones is a Mathematica notebook; basically anything I can turn into PDF is ok. Typical notes are 3-5 pages. I prefer readable prose to outlines or bullet points. Email your notes to me (ruzzo@cs) when you've finished. Please try to do it within one week of class, and please give me a PDF plus your source file(s), including figures, non-standard Latex macros if any, etc., so that I can edit reconstruct a PDF if I edit anything. Portions of the CSE 527 Web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly credited. The CSE 527 Web: © 1993-2005, Department of Computer Science and Engineering, University of Washington.

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