IV106 Bioinformatics seminar

Faculty of Informatics
Spring 2022
Extent and Intensity
0/1/0. 1 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
Mgr. Monika Čechová, Ph.D. (lecturer)
doc. Ing. Matej Lexa, Ph.D. (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
Timetable
Wed 16. 2. to Wed 11. 5. Wed 16:00–16:50 A319
Prerequisites
Those who sign up for this interdisciplinary course should be able to listen to lectures and 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
Course objectives
Long-term the seminar covers "Biological (molecular) and biomedical data analysis". Individual runs may focus on a specific subtopic.
Learning outcomes
Students will gain insight into problems studied in bioinformatics; they will practice presentation and discussion techniques in front of an audience.
Syllabus
  • - Introduction to deep learning in bioinformatics - Lectures of invited lecturers covering the same topic - Students will chose a publication from this area to present in class in a 'journal club' format
Literature
  • ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
Teaching methods
invited lectures, 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/
The course is also listed under the following terms Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, 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 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2022/IV106