Introduction to bioinformatics

Lecturer:

Tomáš Oberhuber (gar.)

Tutor:

Tomáš Oberhuber (gar.)

Supervisor:

Department of Mathematics

Synopsis:

Bionformatics belongs to one of fastest progressing area of the human research. In more general understanding, any nontrivial application of methods from the computer science to biology can be seen as bioinformatics. This course is aimed mainly to analysis of DNA sequences and proteins. However, the algorithms being taught in this course find applications in many other areas.

Requirements:

Basics of algorithms on the level of the course Basics of algoritmization.

Syllabus of lectures:

1. Introduction to molecular biology

2. DNA mapping

3. Motif finding

4. Genome rearrangement (reversal sort)

5-7. Sequence alignment (dynamic programing)

8. Gene prediction

9. DNA sequencing

10. Protein identification

11. Combinatorial pattern matching (suffix trees)

12. Clustering, Hidden Markov Models

Syllabus of tutorials:

1. Reversal sort

2. Dynamic programming

3. Suffix trees

4. Clustering

Study Objective:

Knowledge:

DNA mapping, DNA sequencing, comparing sequences, genes prediction, proteins identification, motif finding, phylogenetic trees reconstruction, dynamic programming, clustering, suffix trees.

Skills:

Student will be able to apply the algorithms being teached to some simple problems in DNA sequence or protein analysis. These algorithms can be also used for advanced text and data set processing.

Study materials:

Key references:

N. C. Jones, P. A. Pevzner, An introduction to bioinformatics, MIT Press, 2004.

Recommended references:

W.-K. Sung, Algorithms in bioinformatics - a practical introduction, CRC Press, 2010.

Media and tools:

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

Time-table is not available yet

The course is a part of the following study plans: