Course for international guest/part time students
- Faculty
- Faculty of Science
- Organization
- TTK Department of Genetics
- Code
- bioinfub17gm
- Title
- Bioinformatics PR
- Usual semester
- Autumn
- Published semester
- 2026/27/1
- ECTS
- 4
- Language
- en
- Learning outcomes
- Competencies: - Knowledge: o Knows the contents of the main biological (sequence, genomic, protein) databases. o Knows of the main bioinformatics file formats. o Knows of the basics of network and systems biology, able to visualise and analyse networks. o Understands the bioinformatics algorithms used. o 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. o Has a systematic scientific knowledge. o Knows the connections between the knowledge acquired in different subjects, understands the importance of an interdisciplinary approach. - Ability: o Finds the information in the main biological databases and able to download files from them. o Able to search and align sequences based on similarity. o Able to infer phylogenetic trees based on homologous sequences. o Able to use software for bioinformatics analysis. o Able to express him/herself professionally both orally and in writing on bioinformatics and high-throughput genetic methods. o Able to organise, analyse and evaluate data and knowledge sets according to scientific criteria. o Able to identify and integrate knowledge and knowledge from different scientific disciplines. - Attitude: o Adheres to and makes others to follow the rules of research ethics. o 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. o 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. o Committed to quality work, sets a high standard to the scientific knowledge and advancement of himself and fellow researchers. o Provides responsible opinions on biological, bioinformatics and high-throughput methodological issues in professional and non-professional forums. o Maintains a state-of-the-art computing environment, facilitating continuous methodological and technological innovation to work more efficiently. - Autonomy and Responsibility: o Expresses views on biological, bioinformatics and high-throughput method issues responsibly in professional and non-professional circles. o Maintains a modern computer environment and helps continuous methodological and technological renewal in order to work as efficiently as possible.
- Course content
- The course aims at implementing classical bioinformatics and modern high-throughput methods of data processing, learning about biological databases, performing molecular phylogenetic calculations, applying neural networks, and predicting and visualising protein structures. The most important topics of the practical: (1) Application of molecular biology databases, (2) The basics of similarity searching and aligning sequences, (3) Molecular phylogenetics in practice, (4) Genome database and browser, (5) Analysis of microarray and RNA-seq data, (6) Application of the Cytoscape network analyser software, (7) Introduction of the application of neural networks, (8) Predicting protein structures, (9) Finding and visualising protein structures, (10) Creating a project work in groups.
- Assessment method
- gy5 = practice mark (5) (1 fail, 5 excellent) Students work in groups of three on a project, where they summarise and analyse the results of the practicals during the semester, and solve related, new bioinformatical problems. They submit a written document on this.
- Bibliography
- exercise descriptions, videos, questionnaires (a fast-changing field, updated every year)