Practical Classes in Bioinformatics I - M143010
Title: Praktikum z bioinformatiky I
Guaranteed by: Department of Informatics and Chemistry (143)
Faculty: Faculty of Chemical Technology
Actual: from 2019
Semester: winter
Points: winter s.:2
E-Credits: winter s.:2
Examination process: winter s.:
Hours per week, examination: winter s.:0/2, MC [HT]
Capacity: unknown / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Znamenáček Jiří Ing.
Class: Základní laboratoře
Examination dates   Schedule   
Annotation -
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)
Aim of the course -

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)
Literature -

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)
Learning resources -

web pages of the course at

Last update: Znamenáček Jiří (14.02.2018)
Requirements to the exam -

A graded credit: homeworks

Last update: Znamenáček Jiří (14.02.2018)
Syllabus -

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)
Registration requirements -

Basic knowladge of bioinformatics and Python programming is assumed.

Last update: Znamenáček Jiří (22.02.2018)
Course completion requirements -

Students will be graded by the work done on home exercises.

Last update: Znamenáček Jiří (14.02.2018)
Teaching methods
Activity Credits Hours
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Účast na seminářích 1 28
2 / 2 56 / 56
Coursework assessment
Form Significance
Regular attendance 20
Homework preparation 80