Teaching code

4S02701

Credits

6

Coordinator

Nicola Vitulo

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/10 - BIOCHEMISTRY

Moodle Seminars 0

The teaching is organized as follows:

Learning objectives

The course aims to introduce the student to bioinformatics, providing basic notions basically focused on the analysis of both nucleotide and protein sequences. The course will provide both theoretical and practical bases of algorithms, programs and methods for searching and analyzing sequence data con-tained in biological databases. At the end of the course students will be able to: Navigate among different biological databases and know how and where retrive the data Analyze sequence data by searching similarity in database Compare, analyze and manage sequence data using different types of programs for sequence align-ments.

Prerequisites and basic notions

Basic knowledge of biology (DNA, proteins). No specific prerequisites are required regarding bioinformatics topics.

Program

The course is divided into two modules, the first more focused on the management and analysis of sequence data, the second on structural biology. The topics covered from a theoretical point of view are accompanied by practical computer exercises, to allow students to put into practice the notions that have been studied during the classes.
Module 1
1. Introduction to bioinformatics
2. Biological databases: primary and secondary databases, search methods in biological databases.
3. Substitution matrix BLOSUM and PAM
4. Introduction to pairwise sequence alignment: dot matrix, algorithm based on dynamic programming (Smith-Watermann, Needlman-Wunsch) , heuristic programs (BLAST and FASTA)
5. Multiple alignments: introduction to multiple alignment algoritms (clustalW and T-Coffee). Positional weight matrices, PSI-BLAST and methods based on Hidden Markov Model (HMM)
6. Introduction to phylogenetic analysis and phylogenetic trees
Module 2
7. Introduction to structural biology. Experimental techniques, amino acids and their physico-chemical properties
8. Protein folding. Introduction to force-fields and energy optimization.
9. Computational methods for studying the secondary and tertiary structures of proteins
(homology modelling and machine learning)
10. Molecular docking applied to in silico drug design techniques

Bibliography

Didactic methods

The course consists of:
- theoretical frontal lessons
- computer exercises to put into practice what has been learned during the theoretical lessons

Learning assessment procedures

The topics covered in the two modules will be assessed in a single exam. The exam consists of 6 open questions (3 for module 1, 3 for module 2) The exam consists of a written test that aims to verify the level of knowledge acquired relating to the topics covered in the course. The student will have to demonstrate that they understand the functioning and application of the main bioinformatics programs and approaches explained in class.

Evaluation criteria

Some relevant criteria will be considered during the verification of the acquired knowledge:
- understanding of the subject;
- ability to connect different topics;
- ability to provide concise and clear answers to the questions;
- use of appropriate scientific terms

Criteria for the composition of the final grade

Each question is assigned a maximum score of 10 points scaled to 32

Exam language

Italiano