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 16, 2020 Jul 16, 2020
Sessione Autunnale. Oct 15, 2020 Oct 15, 2020
Sessione Invernale. Mar 18, 2021 Mar 18, 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

A B C D F G L M P S

Accordini Simone

simone.accordini@univr.it +39 045 8027657

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bicego Manuele

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

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

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

Cicalese Ferdinando

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

Combi Carlo

carlo.combi@univr.it 045 802 7985

Constantin Gabriela

gabriela.constantin@univr.it 045-8027102

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

Delledonne Massimo

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

Franco Giuditta

giuditta.franco@univr.it +39 045 802 7045

Giacobazzi Roberto

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

Giugno Rosalba

rosalba.giugno@univr.it 0458027066

Laudanna Carlo

carlo.laudanna@univr.it 045-8027689

Liptak Zsuzsanna

zsuzsanna.liptak@univr.it +39 045 802 7032

Malerba Giovanni

giovanni.malerba@univr.it 045/8027685

Marcon Alessandro

alessandro.marcon@univr.it +39 045 802 7668

Maris Bogdan Mihai

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

Perduca Massimiliano

massimiliano.perduca@univr.it +39 045 802 7984

Sala Pietro

pietro.sala@univr.it 0458027850

Salvagno Gian Luca

gianluca.salvagno@univr.it 045 8124308-0456449264

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
Final exam
24
E
-

2° Year

ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
English B2
4
F
-
Between the years: 1°- 2°
Between the years: 1°- 2°
Other activities
2
F
-

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

4S004557

Coordinatore

Giuditta Franco

Credits

6

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

English en

Period

I semestre dal Oct 1, 2019 al Jan 31, 2020.

Learning outcomes

Knowledge and understanding
The course is designed to first recall basic concepts of traditional computational models, such as formal languages and automata, and then present several models of bio-inspired computing, including bio-molecular algorithms. Main models of natural computing are presented, in terms of computational processes observed in and inspired by nature.

Applying knowledge and understanding
During the course students will aquire the following competences:
Applying basic notions of discrete mathematics (sets, multisets, sequences, trees, graphs, induction, grammars and finite automata) to explain a few computational methods both to process genomic information and to investigate metabolic networks.

Making judgements
Students will develop the required skills in order to be autonomous in the following tasks:
- choose and processing data in large genomic contexts;
- choose the appropriate methodologies and tools for represent biological information in the context of discrete biological models.

Communication skills
The student will learn how to address the correct and appropriate methods and languages for communicating
problems and solutions in the field of computationaql genomics and of biological dynamics. The course aims at developing the ability of the student both to master notions of discrete structures and dynamics, and to deepen his/her notion of Turing computation, in order to extend it to informational processes involving either natural or bio-inspired algorithms. Student's knowledge of all the topics explained in class will be tested at the exam, along with his/her learning and understanding skills.


Lifelong learning skills
Introduction to natural computing, biological algorithms, and life algorithmic strategies.
Basic notions of discrete mathematics and of formal language theory (Chomsky's hierarchy, automata, and computability).
Elements of information theory (information sources, codes, entropy, and entropy divergences, typical sequences, first and second Shannon's theory).
Methods to extract and analyze genomic dictionaries.
Genomic profiles and distributions of recurrent motifs.
Software IGtools to analyze and visualize genomic data.
Computational models of bio-molecular processes, such as DNA self-assembly and membrane computing.
DNA computing and bio-complexity of bio-algorithms.
DNA algorithms to solve NP-complete problems.
MP grammars, networks, and metabolic dynamics.

Program

Introduction to natural computing, life algorithmic strategies, biological algorithms and paradoxes.
DNA computing on double strings, and computational complexity of bio-algorithms
DNA algorithms to solve a couple of NP-complete problems, to extract and generate DNA libraries Methods to extract and analyze genomic dictionaries
Genomic profiles and distributions of recurrent motifs
Software IGtools to analyze and visualize genomic data
Discrete representation of biochemical systems
Metabolic grammars, networks, and related (inverse) dynamics

Computational models for biomolecular and metabolic processes:
Basic data structures to represent chemical reactions, membrane hierarchies, biological interactions
Formal languages and grammars, Chomsky hierarchy
Specific characterization of REG, REC, CF classes
Finite state automata, Turing machines, computational universality and (bio)complexity
A nutshell of information theory.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
Gheorghe Paun, Grzegorz Rozenberg, Arto Salomaa DNA computing: new computing paradigms (Edizione 3) Springer 2013
Alexander Meduna Formal Languages and Computation: Models and Their Applications Auerbach Publications 2014
Vincenzo Manca Infobiotics Springer 2013

Examination Methods

Only for the first exam session (by February), work assignments (e.g. on topics of computational genomics) or seminars (on recent scienti c articles) will be proposed for students who want to improve their performance in the written exam. Afterwards, in all other exam sessions, only oral exams will be allowed.

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Not yet assigned
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
1° 2° Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
1° 2° CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
1° 2° C++ Programming Language D Federico Busato (Coordinatore)
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Corso Europrogettazione D Not yet assigned
1° 2° 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.

Gestione carriere


Graduation


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.