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. 2016/2017

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 sem. Oct 3, 2016 Jan 31, 2017
II sem. Mar 1, 2017 Jun 9, 2017
Exam sessions
Session From To
Sessione invernale Appelli d'esame Feb 1, 2017 Feb 28, 2017
Sessione estiva Appelli d'esame Jun 12, 2017 Jul 31, 2017
Sessione autunnale Appelli d'esame Sep 1, 2017 Sep 29, 2017
Degree sessions
Session From To
Sessione estiva Appelli di Laurea Jul 18, 2017 Jul 18, 2017
Sessione autunnale Appelli di laurea Nov 22, 2017 Nov 22, 2017
Sessione invernale Appelli di laurea Mar 20, 2018 Mar 20, 2018
Holidays
Period From To
Festa di Ognissanti Nov 1, 2016 Nov 1, 2016
Festa dell'Immacolata Concezione Dec 8, 2016 Dec 8, 2016
Vacanze di Natale Dec 23, 2016 Jan 8, 2017
Vacanze di Pasqua Apr 14, 2017 Apr 18, 2017
Anniversario della Liberazione Apr 25, 2017 Apr 25, 2017
Festa del Lavoro May 1, 2017 May 1, 2017
Festa della Repubblica Jun 2, 2017 Jun 2, 2017
Vacanze estive Aug 8, 2017 Aug 20, 2017

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 L M O P Q T U V

Bicego Manuele

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

Buffelli Mario Rosario

mario.buffelli@univr.it +39 0458027268

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

Delledonne Massimo

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

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

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Franco Giuditta

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

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Giugno Rosalba

rosalba.giugno@univr.it 0458027066

Gobbi Bruno

bruno.gobbi@univr.it

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Lovato Pietro

pietro.lovato@univr.it +39 045 802 7035

Masini Andrea

andrea.masini@univr.it 045 802 7922

Menegaz Gloria

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

Muradore Riccardo

riccardo.muradore@univr.it +39 045 802 7835

Oliboni Barbara

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

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

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Villa Tiziano

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

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 language competence-complete b1 level
6
E
-
ModulesCreditsTAFSSD
One course to be chosen among the following
2 courses to be chosen among the following
Other activitites
3
F
-
Prova finale
3
E
(-)

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
English language competence-complete b1 level
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(BIO/18)

3° Year

ModulesCreditsTAFSSD
One course to be chosen among the following
2 courses to be chosen among the following
Other activitites
3
F
-
Prova finale
3
E
(-)

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

4S02709

Credits

12

Coordinatore

Ferdinando Cicalese

The teaching is organized as follows:

Algoritmi per bioinformatica

Credits

6

Period

I sem.

Academic staff

Ferdinando Cicalese

Laboratorio di programmazione ii

Credits

6

Period

I sem.

Academic staff

Alessandro Farinelli

Learning outcomes

------------------------
MM: ALGORITMI PER BIOINFORMATICA
------------------------
The course aims at providing the fundamental (methodological) tools for the design and analysis of algorithms with some emphasis on problems of interests for bioinformatics. In the presentation of the main technique of algorithm design, applications and example will be preferably taken from the area of bioinformatics and computational biology. The course will provide the students with the knowledge and skills necessary to be able to model simple problems in terms of computational problems; to quantify the computational resources necessary to execute an algorithm, hence to compare different algorithmic solutions in terms of their computational cost. In particular, a student who profitably attended the course, will be able to evaluate the applicability and effectiveness of basic algorithmic design techniques to simple computational problems.
------------------------
MM: LABORATORIO DI PROGRAMMAZIONE II
------------------------
Objective of the course is to provide the basic knowledge to develop algorithms that are relevant to bioinformatics using object oriented programming.

Program

------------------------
MM: ALGORITMI PER BIOINFORMATICA
------------------------
Basic definitions: Computational Problems and Algorithms Analysis of algorithms: worst case and average case analysis; Algorithmic complexity: asymptotic notations; basic tools for the analysis of algorithms; solution of recurrences; Algorithms for searching sorting and selection. Data Structure for the implementing a dictionary: queues, heaps, binary search trees, hash tables; Design techniques: divide and conquer; greedy; dynamic programming; Graphs and Graph algorithms: graph traversals, basic connectivity problems, topological sorting
------------------------
MM: LABORATORIO DI PROGRAMMAZIONE II
------------------------
Java implementation of dynamic data structures and relevant algorithms. Recursion. Interfaces and packages. The student will acquire the necessary knowledge through assisted software development and realizing specific projects. Development of algorithms for sorting, search (greedy and exhaustive) and main algorithms on graphs, applied to problems that are relevant to bioinformatics. All the teaching material for this course is available on the course web page hosted on the teachers' web site.

Examination Methods

------------------------
MM: ALGORITMI PER BIOINFORMATICA
------------------------
The exam verifies that the students have acquired sufficient confidence and skill in the use of basic algorithmic design and algorithmic analysis tools. The exam consists of a written test with open questions. The test includes some mandatory exercises and a set of exercises among which the student can choose what to work on. The mandatory exercises are meant to evaluate the student's knowledge of classical algorithms and analysis tools as seen during the course. "Free-choice" exercises test the ability of students to model "new" toy problems and design and analyse algorithmic solutions for it. The exam can also be passed via two midterm tests (structured as the main final exam). The relative weight of the midterm tests is proportional to the part of the course on which their are based. The overall result of the midterm exams is only valid towards the registration at the one of the exams in February session. The grade in "Algorithms" is given by the average of the grades achieved for the module "Algorithms for Bioinformatics" and the grade achieved for the module "Programming Laboratory II".
------------------------
MM: LABORATORIO DI PROGRAMMAZIONE II
------------------------
The grade in "Algorithms" is given by 50% AB + 50% LPII, where AB is the grade in "Algorithms for Bioinformatics" and LPII is the grade in "Programming Laboratory II". LPII = 50% P + 50% L, where P is a project in the lab and L is a lab test. The grade thus generated is registered at the first exam session in February. Alternatively, LPII = 100% EL, where EL is a lab test, hard enough to match the difficulty of P + L, respectively. All tests and projects are individual work. Cheating is strictly forbidden and will determine lowering of grades for all students involved.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
J. Kleinberg, É. Tardos Algorithm Design (Edizione 1) Addison Wesley 2006 978-0321295354
Neil C. Jones, Pavel A. Pevzner An introduction to bioinformatics algorithms (Edizione 1) MIT Press 2004 0-262-10106-8
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein Introduction to Algorithms (Edizione 3) MIT Press 2009 978-0-262-53305-8

Type D and Type F activities

Modules not yet included

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.