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The goal of the course is to get practical knowledge of bioinformatics algorithms using Python programming language.
Last update: Znamenáček Jiří (01.04.2016)
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R: Libeskind-Hadas, Ran; Bush, Eliot: "Computing for Biologists: Python Programming and Principles" R: Jones, Neil C.; Pevzner, Pavel A.: "An Introduction to Bioinformatics Algorithms" A: Stevens, Tim J.; Boucher, Wayne: "Python Programming for Biology: Bioinformatics and Beyond" A: Haddock, Steven H.D.; Dunn, Casey W.: "Practical Computing for Biologists" A: Bassi, Sebastian: "Python for Bioinformatics" Last update: Znamenáček Jiří (01.04.2016)
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Podmínkou udělení klasifikovaného zápočtu je úspěšné naprogramování vybraných variant některých bioinformatických algoritmů. Last update: Znamenáček Jiří (09.10.2015)
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Recursion, memoization, dynamic programming. Finding motifs. Sequence alignment. Clustering. Phylogenetic trees. Last update: Znamenáček Jiří (01.04.2016)
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The course dedicated web pages. Last update: Znamenáček Jiří (01.04.2016)
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Students will be able to: Understand the principles behind the most important bioinformatics algorithms. Recreate known algorithms in Python and develop new ones. Use existing bioinformatics tools for their own work. Last update: Znamenáček Jiří (01.04.2016)
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Knowledge of some programming language (ideally Python), basics of bioinformatics and biochemistry. Last update: Znamenáček Jiří (01.04.2016)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Obhajoba individuálního projektu | 0.5 | 14 | ||
Práce na individuálním projektu | 1.5 | 42 | ||
Účast na seminářích | 4 | 112 | ||
6 / 2 | 168 / 56 |
Coursework assessment | |
Form | Significance |
Defense of an individual project | 100 |