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
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.
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
The course will be evaluated through assignments and a final project
- 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