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Lecture: Bioinformatics I

Lecturers Prof. Dr. Daniel Huson, Dr. Johannes Fischer and Dr. Stefan Henz
Lectures  Mondays 9-11 A301, Sand 1, Wednesdays 12-14, Kleiner Hörsaal, Sand 6/7
Problem sessions
Group A: Tuesdays 14:15 - 15:45, C118, Sand 14.
Group B: Tuesdays 15:00 - 16:30, Seminarraum F116, Sand 6/7.
no sessions on 15.12.09
Target audience
Diploma- and master-students
Modules
See "Modulhandbuch"
Language
English

Contents

Bioinformatics I focuses on concepts, data-structures and algorithms for sequence analysis.

 
Date
Contents
19.10.2009 1. Introduction; 2. Pairwise Alignment: Hirschberg
21.10.2009 Hirschberg-Alignment (ctd.)
26.10.2009
Gotoh-Algo; 3. Multiple Sequence Alignment (MSA)
28.10.2009 MSAs with ILPs (ctd.)
2.11.2009 Optimal MSA; Progressive Alignment; ClustalW; MUSCLE; T-Coffee; DIALIGN; Consensus Sequences; Profiles and Motifs; TransFac; SeqLogos
4.11.2009 4. BLAST; BLAT
9.11.2009 BLAT (ctd.); 5. FASTA
11.11.2009 6. Phylogeny: Introduction; Newick format
16.11.2009 Neighbor-Joining; Jukes-Cantor-Model
18.11.2009
 continued
23.11.2009 continued
25.11.2009 continued
30.11.2009 7. Suffix trees
2.12.2009
continued
7.12.2009
 continued
9.12.2009 8. Motif finding
14.12.2009 Mid-term exam
16.12.2009 9. HMMs
11.1.2010 continued
13.1.2010  6. Gene finding
18.1.2010 10. SVMs +
20.1.2010
continued +
25.1.2010 11. Physical mapping
27.1.2010  continued
1.2.2010 12. Sequencing and assembly
3.2.2010  continued
8.2.2010 13. Population genetics +
10.2.2010 continued +
15.2.2010 Repetitorium
17.2.2010 Final exam

 

Assignments

 

 Scripts

 

Recommended textbooks (but none covers the whole course)

  • Neil C. Jones, Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms. MIT Press, 2004.
  • Dan Gusfield: Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge UP, 1997.
  • Richard Durbin, Sean R. Eddy, Anders Krogh, and Graeme Mitchison: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge UP, 1998.
  • Pierre Baldi, Soren Brunak: Bioinformatics: The Machine Learning Approach. MIT Press, 1998.

 

How to get credit for this course:

 

• Always participate in the weekly problem sessions and present your results regularly.

• Pass the mid-term exam

• Pass the final exam

You may work on and hand-in assignments in groups of up to two people.

Grade determined as follows: 1/3 assignments, 1/3 mid-term exam, 1/3 final exam

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