FI:IV106 Bioinformatics seminar - Course Information
IV106 Bioinformatics seminar
Faculty of InformaticsSpring 2018
- Extent and Intensity
- 0/1/0. 1 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Thu 12:00–12:50 C416
- Prerequisites
- Those who sign up for this interdisciplinary course should be able to read and comprehend a scientific paper or book chapter written in English. Deeper knowledge of algorithm design and programming will allow the particular student to focus more on the biological side of the studied problems or vice versa. Students of non-biological fields should be concurrently enrolled in, or have previously passed IV107 Bioinformatics I. Alternatively they may frequent the course with the consent of the teacher.
- 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 43 fields of study the course is directly associated with, display
- Course objectives
- The Spring Term seminar covers "Biological sequence analysis, protein structure prediction, detection of genes, promoter sequences and other elements".
Students will gain insight into problems studied in bioinformatics; they will practice presentation and discussion techniques in front of an audience. - Syllabus
- Students will chose publications to study recent methods in genomic sequence analysis (using suggested journal articles or other material approved by the teacher). Possible subjects of papers:
- Sequencing data processing
- Gene identification in DNA sequences
- Similarity between sequences
- Motif and pattern searching
- DNA and RNA secondary structure prediction
- Literature
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Teaching methods
- student presentations and discussion
- Assessment methods
- Each student will be evaluated based on his presentation of the studied paper. Those absent from presentations will take an oral exam of topics covered during the semester.
- Language of instruction
- English
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually. - Teacher's information
- http://www.fi.muni.cz/~lexa/
- Enrolment Statistics (Spring 2018, recent)
- Permalink: https://is.muni.cz/course/fi/spring2018/IV106