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Last update: Znamenáček Jiří Ing. (01.04.2016)
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Last update: Znamenáček Jiří Ing. (01.04.2016)
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. |
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Last update: Znamenáček Jiří Ing. (01.04.2016)
R: Compeau, Phillip; Pevzner, Pavel: "Bioinformatics Algorithms: An Active Learning Approach" R: Jones, Neil C.; Pevzner, Pavel A.: "An Introduction to Bioinformatics Algorithms" A: Antao, Tiago: "Bioinformatics with Python Cookbook" 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" |
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Last update: Znamenáček Jiří Ing. (01.04.2016)
The course dedicated web pages. |
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Last update: Znamenáček Jiří Ing. (01.04.2016)
Podmínkou udělení klasifikovaného zápočtu je úspěšné naprogramování vybraných variant některých bioinformatických algoritmů. |
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Last update: Znamenáček Jiří Ing. (01.04.2016)
Solving NP-complete problems. Markov chains. Monte Carlo method. Protein folding prediction. Machine learning. Gene regulatory networks. |
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Last update: Znamenáček Jiří Ing. (01.04.2016)
Successfully finished course "Laboratory Project I". |
Teaching methods | ||||
Activity | Credits | Hours | ||
Účast v laboratořích (na exkurzi nebo praxi) | 6 | 168 | ||
6 / 2 | 168 / 56 |
Coursework assessment | |
Form | Significance |
Regular attendance | 30 |
Defense of an individual project | 70 |