PV269 Advanced methods in bioinformatics

Faculty of Informatics
Spring 2020
Extent and Intensity
2/0/1. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. David Šafránek, Ph.D. (alternate examiner)
Guaranteed by
doc. RNDr. David Šafránek, Ph.D.
Department of Machine Learning and Data Processing - Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing - Faculty of Informatics
Mon 17. 2. to Fri 15. 5. Tue 12:00–13:50 A215
The student is expected to have basic knowlege in bioinformatics. They must have passed IV108. Previous study of IV107, PA052 a PB050 is recommended.
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
Course objectives
To acquire practical skills in bioinformatics beyond the scope of bachelor courses, extending theoretical topics from IV108.
Learning outcomes
The student will be able to choose appropriate computational methods for a given problem; obtain and prepare relevant data; carry out necessary computation using their own or publicly available programs.
  • Genomic sequences
  • - Advanced techniques for NGS data
  • - Sequence motif detection and genome annotation
  • - Advanced work with genome browsers
  • Proteins
  • - Hidden Markov models (HMM)
  • - Protein structure analysis
  • BAUM, Jeremy O. Understanding bioinformatics. Edited by Marketa J. Zvelebil. New York, N.Y.: Garland Science, 2008. xxiii, 772. ISBN 9780815340249. info
Teaching methods
a combination of short lectures and exercises
Assessment methods
Graded exercises; written exam (zk) or project (k)
Language of instruction
Further Comments
The course is taught annually.
The course is also listed under the following terms Spring 2021.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2020/PV269