SubjectsSubjects(version: 852)
Course, academic year 2019/2020
  
Practical Classes in Bioinformatics I - M143010
Title: Praktikum z bioinformatiky I
Guaranteed by: Department of Informatics and Chemistry (143)
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 [hours/week]
Capacity: unknown / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
For type: Master's (post-Bachelor)
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Znamenáček Jiří Ing.
Annotation -
Last update: Znamenáček Jiří Ing. (22.02.2018)
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.
Aim of the course -
Last update: Znamenáček Jiří Ing. (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.

Literature -
Last update: Svozil Daniel doc. Mgr. Ph.D. (05.11.2018)

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

Learning resources -
Last update: Znamenáček Jiří Ing. (14.02.2018)

web pages of the course at http://vyuka.ookami.cz

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

A graded credit: homeworks

Syllabus -
Last update: Znamenáček Jiří Ing. (15.02.2018)

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.

Registration requirements -
Last update: Znamenáček Jiří Ing. (22.02.2018)

Basic knowladge of bioinformatics and Python programming is assumed.

Course completion requirements -
Last update: Znamenáček Jiří Ing. (14.02.2018)

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

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

 
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