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

4S004550

Credits

12

Coordinatore

Ferdinando Cicalese

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

English

The teaching is organized as follows:

Algorithm design

Credits

6

Period

I semestre

Academic staff

Ferdinando Cicalese

Bioinformatics algorithms

Credits

6

Period

II semestre

Academic staff

Zsuzsanna Liptak

Learning outcomes

Students will acquire a wealth of advanced analytic tools which constitute the foundational basis of the algorithmic solution of important problems in bioinformatics Knowledge and understanding The aim of the course is to provide the student with the necessary skills and know-how for the design and analysis of algorithmic solutions to fundamental bioinformatics problems. Applying knowledge and understanding The students will acquire the ability to design algorithmic solutions for typical problems in bioinformatics and computational biology, e.g., analysis of “omics”-data. Making judgements The students will be able to identify the critical structural elements of a problem and the most appropriate approaches to tackle complex problems in bioinformatics. Communication The students will acquire the ability to describe with appropriate precision and clarity, to both experts and non-specialists: a bioinformatics problem, its mathematical model and the corresponding solution. Lifelong learning skills The students will be able to deepen their know-how in bioinformatics autonomously. Based on the topics studied and the knowledge acquired, they will be able to read, understand, and apply material from advanced text-books and scientific article.

Program

------------------------
MM: Algorithm design
------------------------
Fundamental notions of algorithmic analysis and complexity: Brief recap on graph traversals; shortest path problem; minimum spanning tree algorithms; elements of computational complexity and NP-completeness Models of Genome Rearrangement: (i) approximation algorithms for reversal distance model (sorting unsigned permutations); (ii) the Doble Cut and Join model; (iii) Synteny Distance approximation algorithms Models for Physical Map: (i) The Consecutive Ones Property (C1P); (ii) approximation algorithm for the gap minimisation based on the metric TSP (connections to Hamcycle problems and approximation limits of general TSP; 2-approximation of metric TSP) Models for DNA assembly: (i) The Shortest Common Superstring problem (SCS), connections to maximum cost TSP, approximation of the maximum compression via weighted matching; (ii) Eulerian Cycles based assembly; efficient algorithms for the Eulerian path and Eulerian cycle problem. Models for contig assembly: gap-filling via min-cost flow (flow networks and flow decomposition into edge disjoint paths); min-cost circulation; use of min-cost circulation in SCS (max/min matching in bipartite graphs); Information-theoretic models for biological sequence comparisons: elements of information theory and data compression; LZ-parsing; universal compression distance for clustering and comparison of sequences.
------------------------
MM: Bioinformatics algorithms
------------------------
Here is an overview of the topics that will be covered. The topics in brackets may vary. * Introduction Part I: Pairwise Sequence Comparison * Pairwise sequence alignment * String distances * Pairwise alignment in practice: BLAST, Scoring matrices (* RNA secondary structure prediction) Part II: Multiple sequence alignment * exact DP algorithm (* Carillo-Lipman search space reduction) * approximation algorithms, heuristics Part III: Phyogenetic reconstruction * distance based data: UPGMA, NJ * character based data: Perfect phylogeny (PP) (* character based data: Small Parsimony, Large Parsimony) Part IV: Sequence assembly algorithms (* Shotgun sequencing: SCS) * Sequencing by Hybridization and NGS: de Bruijn graphs, Euler tours

Examination Methods

------------------------
MM: Algorithm design
------------------------
The exam verifies that the students can master the fundamental tools and techniques for the analysis and design of algorithms and that they understand how these techniques are employed in the solution of some classical computational problems arising in bioinformatics. 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 grade for the module Algorithm Design is determined by the result of the written test and the result of homework to be solved periodically during the semester. The overall grade for "Fundamental Algorithms for Bioinformatics" is computed by averaging the grades awarded for the two modules.
------------------------
MM: Bioinformatics algorithms
------------------------
Written exam, followed by oral exam. You are only admitted to the oral if you have passed the written exam. The written exam consists of theoretical questions (problems studied, analysis of algorithms studied, mathematical properties, which algorithms exist for a problem etc.), as well as applications of algorithms to concrete examples (computing a pairwise alignment with the DP algorithm etc.) In the oral exam, the student will explain in detail their solutions to the written exam, and show to what extent they have mastered the topics. Students of the Masters in Molecular and medical biotechnology will have separate questions. (The exam is the same for students who follow the course during the semester and those who do not: frequentanti e no).

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Algorithm design J. Kleinberg, É. Tardos Algorithm Design (Edizione 1) Addison Wesley 2006 978-0321295354
Algorithm design H.J. Böckenhauer, D. Bongartz Algorithmic Aspects of Bioinformatics Springer 2007
Algorithm design Neil C. Jones, Pavel A. Pevzner An introduction to bioinformatics algorithms (Edizione 1) MIT Press 2004 0-262-10106-8
Algorithm design V. Mäkinen, D. Belazzougui, F. Cunial, and A.I. Tomescu Genome Scale Algorithm Design (Edizione 1) Cambridge University Press 2015 ISBN 978-1-107-07853-6
Algorithm design J.C. Setubal, J. Meidanis Introduction to Computational Biology Pws Pub Co 1997
Bioinformatics algorithms H.J. Böckenhauer, D. Bongartz Algorithmic Aspects of Bioinformatics Springer 2007
Bioinformatics algorithms Enno Ohlebusch Bioinformatics Algorithms 2013 978-3-00-041316-2
Bioinformatics algorithms Veli Mäkinen, Djamal Belazzougui, Fabio Cunial and Alexandru I. Tomescu Genome-Scale Algorithm Design CUP 2015 978-1-107-07853-6
Bioinformatics algorithms Joao Setubal and Joao Meidanis Introduction to Computational Biology 1997

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.