Bioinformatics
People
Course director
Description
We deal with the most commonly used algorithms in biological applications. The first part of the course is dedicated to data mining algorithms and other classification methods such as markov models and other
Objectives
Knowledge of basic principles of genome analysis Knowledge of basic principles of protein sequence analysis Building of 3D structures of proteins Docking simulations of drug binding to molecular targets.
Teaching mode
In presence
Learning methods
We explore how to use such algorithms to analyse large amount of data (e.g., genome analysis) and to build 3D structures of proteins (e.g., using homology modeling). The last part of the course is focused on molecular docking algorithms and high throughput screening protocols used in virtual screening calculations. LEARNING METHODS Problem-Based Learning and Team-Based Learning Teaching method: frontal lectures + tutorial sessions
Examination information
The course will be evaluated through assignments and a final project
Bibliography
Education
- Master of Science in Artificial Intelligence, Lecture, Elective, 1st year
- Master of Science in Artificial Intelligence, Lecture, Elective, 2nd year
- Master of Science in Computational Science, Lecture, Elective, 1st year
- Master of Science in Computational Science, Lecture, Elective, 2nd year
- PhD programme of the Faculty of Informatics, Lecture, Elective, 1st year