Bioinformatics
Persone
Docente titolare del corso
Descrizione
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
Obiettivi
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.
Modalità di insegnamento
In presenza
Impostazione pedagogico-didattica
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
Modalità d’esame
The course will be evaluated through assignments and a final project
Bibliografia
Offerta formativa
- Master of Science in Artificial Intelligence, Lezione, A scelta, 1° anno
- Master of Science in Artificial Intelligence, Lezione, A scelta, 2° anno
- Master of Science in Computational Science, Lezione, A scelta, 1° anno
- Master of Science in Computational Science, Lezione, A scelta, 2° anno
- Dottorato in Scienze informatiche, Lezione, A scelta, 1° anno