|
|
|
||
The goal of the course is to get practical knowledge of available bioinformatics toolkits and to be able to write some useful bioinformatics Python programs yourself.
Last update: Znamenáček Jiří (22.02.2018)
|
|
||
Students will be able to: Use existing bioinformatics tools for their own work. Understand the principles of the most important bioinformatics challenges. Solve basic bioinformatics problems using Python programming language. Last update: Znamenáček Jiří (22.02.2018)
|
|
||
Students will be graded by the work done on home exercises. Last update: Znamenáček Jiří (14.02.2018)
|
|
||
R: Mareš, Martin; Valla, Tomáš: "Průvodce labyrintem algoritmů". CZ.NIC, 2017. ISBN 978-80-88168-22-5 R: Pilgrim, Mark: "Ponořme se do Python(u) 3". CZ.NIC, 2011. ISBN 978-80-904248-2-1 R: Jones, Neil C.; Pevzner, Pavel A.: "An Introduction to Bioinformatics Algorithms". The MIT Press, 2004. ISBN 978-0262101066 R: Libeskind-Hadas, Ran; Bush, Eliot: "Computing for Biologists: Python Programming and Principles". Cambridge University Press, 2014. ISBN 978-1107642188 A: Antao, Tiago: "Bioinformatics with Python Cookbook". Packt Publishing, 2015. ISBN 978-1782175117 A: Wróblewski, Piotr: "Algoritmy". Computer Press, 2017. ISBN 978-80-251-4126 A: Bassi, Sebastian: "Python for Bioinformatics". Chapman and Hall/CRC, 2009. ISBN 978-1584889298 A: Compeau, Phillip; Pevzner, Pavel: "Bioinformatics Algorithms: An Active Learning Approach". Active Learning Publishers, 2014. ISBN 978-0990374602 A: Stevens, Tim J.; Boucher, Wayne: "Python Programming for Biology: Bioinformatics and Beyond". Cambridge University Press, 2015. ISBN 978-0521720090 A: Haddock, Steven H.D.; Dunn, Casey W.: "Practical Computing for Biologists". Sinauer Associates, 2010. ISBN 978-0878933914 Last update: Svozil Daniel (05.11.2018)
|
|
||
A graded credit: homeworks Last update: Znamenáček Jiří (14.02.2018)
|
|
||
1-2. Data formats in bioinformatics. 3-4. Algorithm complexity I. Recursion, memoization. Dynamic programming. 5-7. Sequence alignment. 8-9. Multiple sequence alignment. 10-12. Markov chains and models. Hidden Markov models. 13-14. Motifs discovery and search. Last update: Znamenáček Jiří (15.02.2018)
|
|
||
web pages of the course at http://vyuka.ookami.cz Last update: Znamenáček Jiří (14.02.2018)
|
|
||
Basic knowladge of bioinformatics and Python programming is assumed. Last update: Znamenáček Jiří (22.02.2018)
|
Teaching methods | ||||
Activity | Credits | Hours | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1 | 28 | ||
Účast na seminářích | 1 | 28 | ||
2 / 2 | 56 / 56 |