PB051 Computational Methods in Bioinformatics and Systems Biology

Faculty of Informatics
Spring 2026
Extent and Intensity
1/1/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Mgr. Monika Čechová, Ph.D. (lecturer)
doc. Mgr. Bc. Vít Nováček, PhD (lecturer)
Guaranteed by
doc. Ing. Matej Lexa, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Prerequisites
Knowledge of elementary biology and informatics notions. Previous undertaking of courses PA052 and IB113 is expected, but not required formally.
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 38 fields of study the course is directly associated with, display
Course objectives
At the end of the course students 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)
Learning outcomes
At the end of the course students should be able to:
- select appropriate computational methods for a given problem;
- analyse selected types of experimental data;
- apply software tools to selected problems of data processing;
- construct and modify qualitative models of biological networks.
Syllabus
  • The course will be divided into two parts, in each part students will focus on 1-2 areas:
  • Bioinformatics:
  • - collection and preparation of sequences,
  • - determination of consensus sequence,
  • - analysis of sequence occurrence in genomes, genome annotation,
  • - mapping annotation to protein structure
  • Systems biology:
  • - reconstruction of biological networks using data mining,
  • - data integration through biological networks,
  • - static analysis of biological networks, use of gene ontology,
  • - genetic regulatory networks, gene expression analysis,
  • - basics of inference and analysis of qualitative models of biological networks.
  • For all techniques discussed, students will become familiar with relevant tools in the form of practical exercises (hands-on).
Literature
    recommended literature
  • KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
    not specified
  • 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
  • WILKINSON, Darren James. Stochastic modelling for systems biology. Boca Raton: Chapman & Hall/CRC, 2006, 254 s. ISBN 1584885408. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
Teaching methods
A combination of lectures and practical computer exercises.
Assessment methods
Selected evaluated exercises; oral exam
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught every week.
The course is also listed under the following terms Spring 2010, 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 2026, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2026/PB051