Topics in Computational Biology and Genomics |
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Topics in Genomics and Computational Biology is a lecture and discussion course offered by the Departments of Plant and Microbial Biology, Molecular and Cell Biology and Bioengineering of the University of California at Berkeley (it is listed as C146 for undergraduates and C246 for graduate students in all departments). The course is 4 units and meets every Tuesday and Thursday in 241 Cory Hall from 11:00 to 12:30. Auditors are welcome but are expected to participate fully in the class. This year's course will focus on sequence analysis methods. We will begin with the evolutionary foundations of sequence analysis, and will then cover sequence alignment methods, homology based inference of protein function, motif discovery, molecular phylogenetics and comparative sequence analysis. The course is intended for graduate students or undergraduates who wish to obtain a solid understanding of the principles of modern sequence analysis methods and when and where they can and should be applied. This course is not meant for students only wishing to know how to use sequence analysis software. Students taking the class are expected to be able to write simple computer programs to test and explore concepts covered in class. AnnouncementsProjects are due MAY 10 (not May 5) 3 Mar 2005 - Problem set 6 is available. 2 Mar 2005 - Midterm is March 10. Here's a practice exam from 2003. 27 Feb 2005 - Readings for Tuesday's lecture have been added. Reminder: problem set 5 is due tomorrow, the 28th, at midnight. 15 Feb 2005 - Problem set 5 is available. It and problem set 4 are due Monday, Feb 21. Also, solutions for problem set 1 are here at last! 12 Feb 2005 - Reminder: problem set 4 is not due until Monday, Feb 21. Also, many new, optional readings on alignment statistics have been posted under Lecture 7 on the readings page. Some are very useful background information. 8 Feb 2005 - The fourth problem set is available, and readings for the next few lectures have been added. 4 Feb 2005 - A review of linear-space alignment methods, for those interested |
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