AG 3: Teaching
AG 3: Teaching |
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Teacher: Thomas Lengauer
Tutor: Lars Kunert
Course language: The course will be taught in English
| Course: | Tuesday 14-16, Building 45, Lecture Hall 001; Thursday 14-16, Building 45, Lecture Hall 001; starting on Tuesday, April 9, 2002. | ||||
| Tutorial: | Monday 11-13, Building 45, Seminar Room 015; starting on Monday, April 15, 2002. | ||||
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This course is directed towards students that know the basics of computer science, especially of algorithms and statistics, and have some basic knowledge of biology (high school level). Typically students in the course should be fifth semester upward. Students can come from both a biology and a computer science background. The course builds on the course Bioinformatik I given by Hans-Peter Lenhof in WS 2001/2002. People that did not take the WS 2001/2002 course will have to work up on their own some of the basic material on sequence alignment and phylogeny during the SS 2002 course. Nevertheless, with high motivation and appropriate time commitment, the course may be also able to be taken without having attended the winter class.
Homework assignments will be made available every Thursday on this page. Please return your solutions within ten days, at the latest in the beginning of the second next tutorial to Lars Kunert. For those students that get 2/3 of the maximum number of points possible for the homework assignments, there will be a final oral exam at the end of the course period.
The course concentrates on "downstream" problems in computational biology, i.e. those problems that arise after the basic genome and protein sequence has been analyzed. (These latter problems were the focus of the WS 2001/2002 course.) Problems that are covered include protein structure comparison, protein structure prediction, protein domain and protein family analysis, protein function analysis, analysis of protein interactions (docking), drug comparison and drug screening, analysis of mRNA expression data, analysis of metabolic and regulatory networks, analysis of genetic variations, analysis of resistance patterns in infectious diseases.