FI:PV269 Adv. methods in bioinformatics - Course Information
PV269 Advanced methods in bioinformatics
Faculty of InformaticsSpring 2025
- Extent and Intensity
- 2/0/1. 3 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. (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 - Prerequisites
- 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
- there are 37 fields of study the course is directly associated with, display
- 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.
- Syllabus
- 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
- Literature
- Next-generation DNA sequencing informatics. Edited by Stuart M. Brown. Second edition. Cold Spring Harbor: Cold Spring Harbor Laboratory Press, 2015, xiv, 402. ISBN 9781621821236. info
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- a combination of short lectures, exercises and homework
- Assessment methods
- Graded exercises; written exam (zk) or project (k)
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (Spring 2025, recent)
- Permalink: https://is.muni.cz/course/fi/spring2025/PV269