PB051 Computational methods in Bioinformatics and Systems Biology

Faculty of Informatics
Spring 2010
Extent and Intensity
1/1. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Mgr. Vojtěch Bystrý, Ph.D. (seminar tutor)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Tue 8:00–9:50 B130
Prerequisites
Knowledge of elementary molecular biology and basic problems in bioinformatics and systems biology is expected.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 22 fields of study the course is directly associated with, display
Course objectives
At the end of the course the student should be able to: select appropriate methods for a given problem; obtain and prepare necessary data; analyse the data (using their own program or publically available solutions)
Syllabus
  • The course will be divided into two parts, each will cover 1-2 methods:
  • Bioinformatics:
  • operations on genomes
  • using Markov models
  • Systems biology:
  • biological network analysis by graph-theoretical methods
  • computational methods for simulation of biological systems dynamics
Literature
  • ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
  • Systems biology : principles, methods, and concepts. Edited by Andrzej K. Konopka. Boca Raton: CRC Press, 2007, 244 s. ISBN 9780824725204. info
Teaching methods
A combination of lectures and practical computer exercises.
Assessment methods
Seleced evaluated exercises; written exam
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2010, recent)
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