Bioinformatics

biology
biotechnology
chemistry
computer science
physics

general courses

Enrolled students should be aware of central dogma of molecular biology; understand replication, transcription and translation processes as well as the genetic code

Classroom

Learning of practical skills with basic bioinformatics tools and Internet services and programming of simple practical tasks and computer visualization of the results

The aim of this course is to provide a wide overview of bioinformatics methods working on sequence and structural data.

Lots of attention will be put to understanding the basis of bioinformatics. The most popular web-services, software and databases will be presented

1) Introduction

What is bioinformatics. Its role and importance in biology, medicine, pharmacology, biotechnology and drug design.

2) Bioinformatical databases

GenBank, SwissProt, PDB, PFAM and other databases, hosting sequences, structures and annotations. The issues of data quality, redundancy and completness. The most popular file formats (PDB, FASTA)

3) Structure visualization Pymol, VMD and other popular software

4) Optimal sequence alignment

Computational complexity of the problem. Differences between local and global alignment. Gap penalty model, substitution matrices. The problem of alignment significance estimation: alignment score, e-value, p-value, z-score, sequence identity

5) Homology and protein families

The concepts of a homolog, paralog, ortholog and analog.

6) Heuristical sequence alignment methods and adta base search: FASTA and BLAST

7) Multiple sequence alignments (MSA)

Computational complexity of the problem, example heuristical methods: CLUSTAL, mafft, muscle. Phylogenetic trees. Bazy danych PROSITE and PFam databases.

8) Sequence profiles: significance and applications

Hidden Markov Models (HMM). PsiBlast, HMMER, HHSearch programs. Alignment of sequence profiles (1D threading)

9) Analysis and comparison of protein structures

Optimal structure superimposition. Mean root square coordinate difference (crmsd). methods for definition (DSSP) and prediction of secondary structure (PsiPred)

10) Predicting protein structure and function

Different concepts for protein threading. Servers and metaservers. Comparative modeling and de novo approach.

Popular software: Rosetta, SWISS-MODEL i MODELLER. Ligand docking and structure based drug design

1. A. D. Baxevanis, B.F. F. Ouellettee, Bioinformatics, Wiley 1998

2.J. Setubal, J. Meidanis, Introduction to Computational Biology, PWS Publishing, 1997

3.E. V. Koonin, M. Y. Galperin, Sequence-Evolution-Function, Computational Approaches in Compartive Genomics, Kluwer, 2003

Student posses general knowledge of the basic problems and techniques of bioinformatics (sequence and structure databases, sequence and structure comparisons, computational methods of bioinformatics). Practical knowledge of applications of bioinformatics in molecular modeling of proteins and nucleic acids, in particular a student can:

- find a given structure in the PDB and collect necessary informations about it

- calculate an alignment between two sequences

- find homologues sequences in databases; restrict the search by various criteria

- assign a protein to a protein family; both according to its structure and sequence

- find plausible templates for comparative modeling

- build a structural model of a query protein by means of comparative modeling

Written test, containing 15 closed questions and 5 open questions, conducted off-line (in a class room) or an oral exam - possibly online

does not concern