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Bioinformatics

Description

COURSE 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

 

COURSE 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 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
Teaching method: frontal lectures + tutorial sessions Problem-Based Learning Team-Based Learning

 

EXAMINATION INFORMATION
The course will be evaluated through assignments and a final project

 

REFERENCES

  • Notes from the course - Essential Bioinformatics by Jin Xiong

People

 

Limongelli V.

Course director

Additional information

Semester
Fall
Academic year
2020-2021
ECTS
6
Language
English
Education
Master of Science in Computational Science, Core course, Lecture, 2nd year