Course for international guest/part time students

Faculty

Faculty of Science

Organization

TTK Department of Genetics

Code

bioinfub22em

Title

Bioinformatics L

Usual semester

Autumn

Published semester

2026/27/1

ECTS

3

Language

en

Learning outcomes

Competencies: knowledge: Knows the main biological databases, the basis of network- and systems biology. Understands the classical and the high-throughput bioinformatic methods. Knows the fields of application of modern biological research methods, understands the importance of the development of these methods, and contributes to it as much as possible. Has a systematic scientific knowledge. Knows the connections between the knowledge acquired in different subjects, understands the importance of an interdisciplinary approach. Ability: Able to express oneself professionally, both in oral and written form in the field of bioinformatics and high-throughput genetics. Able to systematize data and knowledge, analyse and evaluate them according to scientific aspects. Can recognize and integrate connections between the knowledge of different scientific fields. Attitude: Adheres to and makes others to follow the rules of research ethics. Actively disseminates the results of the field of science, confidently publishes knowledge even in the media, and defends his/her professional position against representatives of other approaches and pseudoscience, if necessary. Open to new biological and other scientific research results and scientific cooperation. Seeks to further develop existing results and actively promotes the development of new research directions. Committed to quality work, sets a high standard to the scientific knowledge and advancement of himself and fellow researchers. Autonomy and responsibility: Expresses views on biological, bioinformatics and high-throughput method issues responsibly in professional and non-professional circles. Maintains a modern computer environment and helps continuous methodological and technological renewal in order to work as efficiently as possible.

Course content

The aim of the course is to provide a view about the classical bioinformatics, the data processing methods of the high-throughput experiments, and the biological databases. The most important topics of the practical: (1) Biological databases, (2) Sequence alignment, (3) Sequence similarity searches, (4) Molecular phylogenetic methods, (5) Genomics, (6) Transcriptomics, (7) Structural bioinformatics, (8) Network biology, (9) Systems biology.

Assessment method

k5 = exam mark (5) (1 failed, 5 excellent) Students write more written exams during the semester. The lecture mark is the mean of the results of these exams.

Bibliography

Lecture slides, description of the practical tasks (rapidly changing field, updated every year).

Programmes of the course