Introduction to computational biology

elective monographs

The aim of this course is to introduce students with a computer science and mathematics background to data-driven problems from molecular biology (we will focus on analysis of protein and nucleic acid sequences). In this course we will present some of the mathematical models and computational methods used today in molecular sequence analysis.

1. Short introduction to molecular biology (nucleic acids, proteins, transcription, translation, experimental techniques). (2 lectures).

2. Sequence alignment (global -- Needelman Wunsh algorithm and local -- Smith-Watermann algorithm). (2 lectures).

3. Amino acid substitution matrices (PAM, BLOSUM), efficient sequence comparison methods (BLAST, FASTA), Statistical significance of alignment scores. (3 lectures).

4. Hidden Markov Models (Viterbi and Baum-Welch method) with applications. (2 lectures).

5. Multiple alignment (dynamic programming, `star alignment', `tree alignment'), profile analysis, approximation algorithms, progressive alignment (CLUSTALW), Tcoffee, MAFFT( 2 lectures).

6. Genome-scale alignment. (1 lecture).

7. Introduction to phylogenetics. (2 lectures).

The course will be given in Polish, if no non-polish speaking students register for it.

1. A. Malcolm Campbell. Laurie J. Heyer, Discovering Genomics, Proteomics, and Bioinformatics, Pearson Education 2003,

2. R. Durbin, S. Eddy, A. Krogh, G. Mitchson, Biological Sequence Analysis, Cambridge Univ. Press, 1997.

3. P. Pevzner, Computational Molecular Biology, The MIT Press, 2000

4. Ewens, W.J. and Grant, G., Statistical Methods in Bioinformatics, Springer-Verlag, 2001

knowledge:

1. Student has a general knowledge of the problems of computational biology.

2. Student has a basic knowledge of the mathematical tools used in the modeling and analysis of molecular data.

skills:

1. Student can perform a simple bioinformatic analysis for molecular sequences.

2. Student can use advanced bioinformatics tools.

competence:

1. knows his own limitations of knowledge and understands the need for further education (K_K01)

2. is able to manage their time and make commitments and meet deadlines (K_K05)

3. can use the interdisciplinary literature

Programming assignments,

written test,

Oral exam.