Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

A.A. 2019/2020

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I semestre Oct 1, 2019 Jan 31, 2020
II semestre Mar 2, 2020 Jun 12, 2020
Exam sessions
Session From To
Sessione invernale d'esame Feb 3, 2020 Feb 28, 2020
Sessione estiva d'esame Jun 15, 2020 Jul 31, 2020
Sessione autunnale d'esame Sep 1, 2020 Sep 30, 2020
Degree sessions
Session From To
Sessione Estiva Jul 15, 2020 Jul 15, 2020
Sessione Autunnale Oct 16, 2020 Oct 16, 2020
Sessione Autunnale Dicembre Dec 11, 2020 Dec 11, 2020
Sessione Invernale Mar 17, 2021 Mar 17, 2021
Holidays
Period From To
Festa di Ognissanti Nov 1, 2019 Nov 1, 2019
Festa dell'Immacolata Dec 8, 2019 Dec 8, 2019
Vacanze di Natale Dec 23, 2019 Jan 6, 2020
Vacanze di Pasqua Apr 10, 2020 Apr 14, 2020
Festa della Liberazione Apr 25, 2020 Apr 25, 2020
Festa del Lavoro May 1, 2020 May 1, 2020
Festa del Santo Patrono May 21, 2020 May 21, 2020
Festa della Repubblica Jun 2, 2020 Jun 2, 2020
Vacanze estive Aug 10, 2020 Aug 23, 2020

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

B C D F G M O P Q R S T V Z

Ballottari Matteo

matteo.ballottari@univr.it 045 802 7098

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it +39 045 8028827 - 47

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bonnici Vincenzo

vincenzo.bonnici@univr.it +39 045 802 7045

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Capaldi Stefano

stefano.capaldi@univr.it +39 045 802 7907

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Della Libera Chiara

chiara.dellalibera@univr.it +39 0458027219

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Dell'Orco Daniele

daniele.dellorco@univr.it +39 045 802 7637

Dominici Paola

paola.dominici@univr.it 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

mariapina.donofrio@univr.it 045 802 7801

Drago Nicola

nicola.drago@univr.it 045 802 7081

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Paci Federica Maria Francesca

federicamariafrancesca.paci@univr.it +39 045 802 7909

Piccinelli Fabio

fabio.piccinelli@univr.it +39 045 802 7097

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Romeo Alessandro

alessandro.romeo@univr.it +39 045 802 7974-7936; Lab: +39 045 802 7808

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

silviafrancesca.storti@univr.it +39 045 802 7908

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Villa Tiziano

tiziano.villa@univr.it +39 045 802 7034

Zivcovich Franco

franco.zivcovich@univr.it

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
English B1
6
E
-
ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(BIO/18)
1 module among the following
6
C
(FIS/07)

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
English B1
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(BIO/18)
1 module among the following
6
C
(FIS/07)

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S003713

Credits

12

Coordinatore

Alejandro Giorgetti

Scientific Disciplinary Sector (SSD)

BIO/10 - BIOCHEMISTRY

Language

Italian

The teaching is organized as follows:

Mod.2 teoria

Credits

3

Period

II semestre

Academic staff

Alejandro Giorgetti

Mod.2 laboratorio

Credits

3

Period

II semestre

Academic staff

Alejandro Giorgetti

Mod.1 teoria

Credits

3

Period

I semestre

Academic staff

Daniele Dell'Orco

Mod.1 laboratorio

Credits

3

Period

I semestre

Academic staff

Daniele Dell'Orco

Learning outcomes

The course will provide the theoretical and practical basis to understand and employ algorithms and programs currently used to retrieve and analyze data contained in the most used biological data repositories. Via group oral presentations, students will also acquire communication and self-evaluation skills.

The course is divided into two modules, as detailed below.



Module 1: In this module student will become acquainted with some of the most used software tools for managing data in proteomics, genomics, biochemistry, molecular and structural biology. Students will be introduced to the analysis and the visualization of structural data of biological macromolecules and their complexes, and to the design of simple static and dynamic models of biomolecular networks. The students will also be introduced to the most modern fields of systems biology.

Module 2: In this module students will learn how to employ the basic bioinformatic tools for the analysis, interpretation and prediction of biological data in proteomics, genomics, biochemistry, molecular biology. This course offers the possibility of applying state of the art bioinformatic tools to solve biological problems.

Program

------------------------
MM: Modulo 1
------------------------
Theoretical Module
- Overview of the main structural features of proteins and nucleic acids in relation to the concept of evolution. Introduction to biomolecular databases: online resources and their use
- Biological databases: organization and integration of information concerning: a) protein and nucleic acid sequences; b) biomolecular structures; c) bibliographic and scientific literature. Retrieve of specific information: use of limitations and Boolean operators.
- Sequence comparison and alignments: static and dynamic algorithms; substitution matrices (PAM,BLOSUM) - Search-algorithms: dynamic algorithms; Smith-Waterman; Needleman-Wunsch; statistic significance for an alignment (z-score, expectation values and probability); heuristic methods for local alignments; BLAST
- Multiple sequence alignments: ClustalW, search on specific databases, other algorithms, PSI-BLAST
- Introduction to Structural Bioinformatics: visualization and analysis of protein and nucleic acid 3D structures
- Methods to predict protein secondary structure elements starting from the sequence; introduction to neural networks. NN-based methods - Introduction to Systems Biology: Spatial and temporal scales, static and dynamic models, mathematical frameworks, introduction on signal transduction networks Laboratory Module
- NCBI databases: Entrez interface, Gene, UniGene, Protein, Uniprot and EBI
- Single and multiple sequence alignments, score matrices, optimal methods; online resources and spreadsheets - BLAST,PSI-BLAST and BLAT: online tools and their use
- Tools for multiple alignments, the Homologene databank, computation and visualization of multiple alignments - Introduction to PyMol and molecular visualization. Use of PSI-PRED and JPRED for predicting secondary structures from sequences - Systems biology: numerical simulation of simple biochemical reactions. Building simple kinetic models by using SBOTOOLBOX2 for Matlab; application to G-potein signalling cycles.

-----------------------
MM: Modulo 2
------------------------
Bioinformatic tools for the analysis of molecular evolution and phylogenesis: Molecular clock, substitution models, methods for the construction of phylogenetic trees.
Protein structural predictions: Comparative modeling, Fold recognition and ab initio methods.
Gene prediction Functional annotation Microarrays: databases and programs for the analysis of expression data. Introduction to the energetic treatment of proteins: MD simulations, ligand-protein and protein-protein docking.
The teaching includes: front lectures and hands-on laboratories on the PC. The students are also involved in a project to be developed in groups.

Examination Methods

------------------------
MM: Modulo 1
------------------------
In order to pass the examination, students shall demonstrate: - to understand the concept of homology and its practical implications in bioinformatics - to understand the difference between similarity and identity of biological sequences - to know how to query bioinformatics databases, in order to obtain and store relevant data and to conduct appropriate cross-searches on different databases - to know how to use algorithms for comparison of nucleotide and amino acid sequences - to know how to use software for molecular graphics and visualization - to know how to build simple interaction networks of biomolecules and simulate their time course.
Theory:
The exam consists of a written test with 5 open questions on the topics discussed in the course. Each correct question will score a maximum of 6 points. The test will last 75 minutes.
Laboratory :
The exam, which can be given on the same day of the theory part, is made of 3 exercises to be solved using the computer (each one has a maximum 10 points-score). The test will last 75 minutes.
Presentations:
At the end of January, groups of 2 or 3 students will present a database of their choice, which has been described in the January issue of Nucleic Acids Research (Database issue). A10 minute presentation (+ 3 minute for questions / discussion) shall be given, illustrating the database goals and an original test-case. Presentation will be given a score of 1 to 4, taking into account the depth of the presented subject, clarity and effectiveness of communication and mastery of the tools used.
Final score : The final score, in thirty's (/30), will be given by the average score of the theoretical and laboratory part, plus the score for the presentation.

------------------------
MM: Modulo 2
------------------------
The written exam is divided in two: a session of open questions regarding the theoretical arguments of the course: modelling, docking and gene annotation. The second phase consists in the preparation of a scientific-like article presenting the results obtained during the project development

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Mod.2 teoria Stefano Pascarella e Alessandro Paiardini Bioinformatica Zanichelli 2011 9788808062192
Mod.2 teoria Frishman, D., Valencia, Alfonso Modern Genome Annotation Springer 2008
Mod.2 laboratorio Stefano Pascarella e Alessandro Paiardini Bioinformatica Zanichelli 2011 9788808062192
Mod.2 laboratorio Frishman, D., Valencia, Alfonso Modern Genome Annotation Springer 2008
Mod.1 teoria Stefano Pascarella e Alessandro Paiardini Bioinformatica Zanichelli 2011 9788808062192
Mod.1 teoria Jonathan Pevsner Bioinformatics and Functional Genomics, 3rd Edition Wiley-Blackwell 2015 978-1-118-58178-0
Mod.1 laboratorio Stefano Pascarella e Alessandro Paiardini Bioinformatica Zanichelli 2011 9788808062192
Mod.1 laboratorio Jonathan Pevsner Bioinformatics and Functional Genomics, 3rd Edition Wiley-Blackwell 2015 978-1-118-58178-0

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
C++ Programming Language D Federico Busato (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Corso Europrogettazione D Not yet assigned
The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Matteo Cristani

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Graduation

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

Gestione carriere


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.