English

Not applicable.

The home faculty only

The subject knowledge on the Bachelor's degree level is requested.

Students have to obtain at least 50 points out of 100 in the sub-activities:
1. midterm test (max. 30 points),
2. final test (max. 30 points),
3. implementation of algorithms (min 20 points, max 40 points).
Individual activities check students' ability to implement algorithms in chosen programming language.
Computer exercises are mandatory, properly excused missed lectures can be compensated individually after discussion with teacher.

The aim of the course is introduction to algorithms for analyzing DNA and protein sequences and their detailed analysis. Students program the discussed algorithms in programming environment R.
Student is able to:
- Solve problems iteratively and recursively
- Evaluate the performance of algorithms
- Implement algorithms for searching (brute force, branch-and-bound, greedy algorithms)
- Implement algorithms for sequence alignment using dynamic programming with recursion
- Implement algorithms for learning hidden Markov models and their use

Not applicable.

Not applicable.

Chao K.-M., Zhang L.: Sequence Comparison. Springer-Verlag, 2009
Jones N.C., Pevzner P.A: An Introduction to Bioinformatics Algorithms. The MIT Press, 2004
Moorhouse M, Barry P: Bioinformatics Biocomputing and Perl: An Introduction to Bioinformatics Computing Skills and Practice. Wiley; 1 edition, 2004.
Zaplatílek K, Doňar B: Matlab tvorba uživatelských aplikací, Technická literatura BEN, Praha 2004

Not applicable.