Programming in Bioinformatics
FEKT-MPA-PRGAcad. year: 2022/2023
The course is oriented to programming in bioinformatics area. It studies introduction to programming and alghoritms used for DNA and protein sequence analysis.
Offered to foreign students
Learning outcomes of the course unit
- 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
Recommended optional programme components
Moorhouse M, Barry P: Bioinformatics Biocomputing and Perl: An Introduction to Bioinformatics Computing Skills and Practice. Wiley; 1 edition, 2004.
Chao K.-M., Zhang L.: Sequence Comparison. Springer-Verlag, 2009
Zaplatílek K, Doňar B: Matlab tvorba uživatelských aplikací, Technická literatura BEN, Praha 2004
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
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.
Language of instruction
2. Types of algorithms, recursion and iteration.
3. Regular expressions.
4. Sorting algorithms (greedy algoritmy).
5. Restriction mapping (exhaustive search).
6. Motive search (branch and bound algorithms).
7. Dynamic programming with recursion.
8. Algorithms for de novo genome assembly.
9. Markov models in bioinformatics.
10. Suffix trees.
Specification of controlled education, way of implementation and compensation for absences
Classification of course in study plans
- Programme MPC-BTB Master's, 1. year of study, winter semester, 5 credits, compulsory