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.

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, 2018 Jan 31, 2019
II semestre Mar 4, 2019 Jun 14, 2019
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2019 Feb 28, 2019
Sessione estiva d'esame Jun 17, 2019 Jul 31, 2019
Sessione autunnale d'esame Sep 2, 2019 Sep 30, 2019
Degree sessions
Session From To
Sessione Estiva Jul 18, 2019 Jul 18, 2019
Sessione Autunnale Oct 17, 2019 Oct 17, 2019
Sessione Invernale Mar 18, 2020 Mar 18, 2020
Holidays
Period From To
Festa di Ognissanti Nov 1, 2018 Nov 1, 2018
Sospensione dell'attività didattica Nov 2, 2018 Nov 3, 2018
Festa dell’Immacolata Dec 8, 2018 Dec 8, 2018
Vacanze di Natale Dec 24, 2018 Jan 6, 2019
Vacanze di Pasqua Apr 19, 2019 Apr 28, 2019
Festa della liberazione Apr 25, 2019 Apr 25, 2019
Festa del lavoro May 1, 2019 May 1, 2019
Festa del Santo Patrono May 21, 2019 May 21, 2019
Festa della Repubblica Jun 2, 2019 Jun 2, 2019
Vacanze estive Aug 5, 2019 Aug 18, 2019

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 G L M P S

Accordini Simone

symbol email simone.accordini@univr.it symbol phone-number +39 045 8027657

Belussi Alberto

symbol email alberto.belussi@univr.it symbol phone-number +39 045 802 7980

Bicego Manuele

symbol email manuele.bicego@univr.it symbol phone-number +39 045 802 7072

Bombieri Cristina

symbol email cristina.bombieri@univr.it symbol phone-number 045-8027284

Bombieri Nicola

symbol email nicola.bombieri@univr.it symbol phone-number +39 045 802 7094

Boscaini Maurizio

symbol email maurizio.boscaini@univr.it

Busato Federico

symbol email federico.busato@univr.it

Calanca Andrea

symbol email andrea.calanca@univr.it symbol phone-number +39 045 802 7847

Cicalese Ferdinando

symbol email ferdinando.cicalese@univr.it symbol phone-number +39 045 802 7969

Combi Carlo

symbol email carlo.combi@univr.it symbol phone-number 045 802 7985

Constantin Gabriela

symbol email gabriela.constantin@univr.it symbol phone-number 045-8027102

Daducci Alessandro

symbol email alessandro.daducci@univr.it symbol phone-number +39 045 8027025

Dall'Alba Diego

symbol email diego.dallalba@univr.it symbol phone-number +39 045 802 7074

Delledonne Massimo

symbol email massimo.delledonne@univr.it symbol phone-number 045 802 7962; Lab: 045 802 7058

Giugno Rosalba

symbol email rosalba.giugno@univr.it symbol phone-number 0458027066

Laudanna Carlo

symbol email carlo.laudanna@univr.it symbol phone-number 045-8027689

Liptak Zsuzsanna

symbol email zsuzsanna.liptak@univr.it symbol phone-number +39 045 802 7032

Malerba Giovanni

symbol email giovanni.malerba@univr.it symbol phone-number 045/8027685

Marcon Alessandro

symbol email alessandro.marcon@univr.it symbol phone-number +39 045 802 7668

Maris Bogdan Mihai

symbol email bogdan.maris@univr.it symbol phone-number +39 045 802 7074

Perduca Massimiliano

symbol email massimiliano.perduca@univr.it symbol phone-number +39 045 802 7984

Sala Pietro

symbol email pietro.sala@univr.it symbol phone-number 0458027850

Salvagno Gian Luca

symbol email gianluca.salvagno@univr.it symbol phone-number 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.

activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
English B2 level
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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S004550

Credits

12

Coordinatore

Ferdinando Cicalese

Language

English en

Also offered in courses:

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

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 (brief recap): graph traversals; shortest paths in graphs; minimum spanning tree; dynamic programming. Elements of computational complexity and NP-completeness Models of Genome Rearrangement: (i) polynomial time algorithm for sorting signed permutations; (ii) approximation algorithms for sorting unsigned permutations; (iii) Synteny Distance Some Fundamental Graph Problems: (i) Graph tours: Hamiltonian Cycles and Eulerian Cycles; efficient algorithms for Eulerian path and Eulerian cycle; (ii) The Traveling Salesman Problem: relationships to the hamiltonian cycle problems; inapproximability of the symmetric TSP; 2 approximation algorithm for the metric TSP Models for Physical Map: (i) polynomial time algorithm for The Consecutive Ones Property (C1P); (ii) approximation algorithm for the gap minimisation based on the metric TSP Models for DNA assembly: The Shortest Common Superstring problem and the approximation of the the maximum compression via weighted matching. Network Flow: maximum flow and min cut problems; maximum matching; decomposition of flow into edge disjoint paths; polynomial time algorithm for the minimum/maximum weight perfect matching in bipartite graphs. Models for Motif Finding: (i) the Consensus String Problem; (ii) Polynomial Time Approximation Scheme. Models of Haplotyping: polynomial time algorithms for the haplotyping problem for single individual on gapless data; extensions and parameterisations in the presence of data with gaps.
------------------------
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 algorithm, 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

Bibliography

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 Dan Gusfield Algorithms on Strings, Trees, and Sequences Cambridge University Press 1997 0 521 58519 8
Bioinformatics algorithms Enno Ohlebusch Bioinformatics Algorithms 2013 978-3-00-041316-2
Bioinformatics algorithms Joao Setubal and Joao Meidanis Introduction to Computational Biology 1997

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.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.

Graduation

Deadlines and administrative fulfilments

For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

Need to activate a thesis internship

For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.

Final examination regulations

Upon completion of the Master’s degree dissertation, students are awarded 24 CFU, which equates to no more than 4-5 months of full-time work. The dissertation may be written and presented in English or Italian, also using multimedia tools such as presentations and videos.

Goals
The primary goal of a dissertation is to develop an original study that may include an application project or a theoretical topic related to specific design issues, or a critical review of the most recent developments in a given field of study. During the preparation of the dissertation, under the guidance of the Supervisor and co-supervisors (if any), the student is expected to conduct an in-depth study of the chosen topic, while gaining the ability to summarise and creatively apply the knowledge acquired. The dissertation should focus on topics of bioinformatics and medical informatics, or closely related areas of study. The work shall consist in the written presentation of activities that may be structured as follows:

  • design and development of applications or systems;
  • critical analysis of contributions from the scientific literature;
  • original research contributions.

The dissertation may be written either in English or in Italian, and can be presented either in English or in Italian, also relying on multimedia tools such as presentations and videos. Should the dissertation be written in Italian, the work will need to include an abstract in English.

Assessment methods and examination procedures
The final examination consists in writing a Master’s degree dissertation, which will engage the student in a work of research, formalisation, design or development, thus contributing to complete their technical and scientific training. Each dissertation can be either internal or external, depending on whether it is carried out at the University of Verona or in collaboration with another institution. For each dissertation a Supervisor, one or more co-supervisors (optional) and an Examiner will be appointed. The Examiner is appointed by the Computer Science Teaching Committee at least 20 days before the presentation of the dissertation, once the student's eligibility to take the Master's degree examination has been verified. With regard to the legal aspects related to the dissertation and its scientific outcomes (e.g. intellectual property of research outcomes), please refer to the relevant legislation and the University Regulations.

Evaluation of the dissertation
The Supervisor, the co-supervisor/s (if any) and the Examiner will evaluate the dissertation based on the following criteria:

  1. level of in-depth analysis carried out, in relation to the most recent developments in the areas related to information technology, with a focus on medical and biological applications;
  2. scientific and/or technological outcomes of the dissertation;
  3. student’s critical thinking;
  4. student’s experimental and/or formal development;
  5. student’s ability to carry out independent work (this point will not be assessed by the Examiner);
  6. value of the methodologies used;
  7. accuracy in planning and writing the dissertation.

Graduation mark
The graduation mark (based on a 110-point scale) is a whole value between 66/110 and 110/110 and is calculated by adding together the following elements (then rounding the result to the nearest whole number, e.g. 93.50 => 94; 86.49 => 86):

  • 1) the average of the marks gained in the modules, weighted according to CFU, converted to a 110-point scale;
  • 2) evaluation of the dissertation and the oral presentation during the final examination, based on the following methods:
    • a) each of the points 1-7 listed above will be assigned a coefficient between 0 and 1 (fractional coefficient with one decimal place);
    • b) the quality of the presentation will be assessed by awarding a coefficient between 0 and 1 (fractional coefficient with one decimal place);
    • c) the sum of the points resulting from (a) and (b).

The Graduation Committee may award one extra point in the following cases: cum laude honours obtained in the exams taken during the degree programme; participation in internships officially recognised by the Computer Science Teaching Committee; taking extra modules; and the achievement of the degree in a time that is shorter than the normal duration of the degree programme. If the final score is 110/110, the Graduation Committee may award cum laude honours by unanimous decision.

External dissertations
An external dissertation is a work carried out in collaboration with an institution/body other than the University of Verona. In this case, the topic of the dissertation must be agreed in advance with a Supervisor from the University of Verona. In addition, the student must indicate at least one co- supervisor belonging to the external institution/body, who will support the student during the work on the dissertation. The Supervisor and the co- supervisors must be indicated in the online graduation application. The insurance aspects relating to the student's stay at the external institution are regulated by the regulations in force at the University of Verona. If the dissertation involves a period of training at the external institution/body, then it is necessary that the University of Verona enters into a specific agreement with such institution/body. The scientific outcomes of the dissertation will be available to all parties involved. In particular, the contents and results of the dissertation are to be considered public. For all matters not strictly scientific (e.g. agreements, insurance) the resolution of the Academic Senate of 12 January 1999 shall be taken as a reference.

Supervisor, co-supervisors, examiners
The dissertation presentation is introduced by the Supervisor. Professors belonging to the Master’s degree programme in Medical Bioinformatics, the Department of Computer Science, and any associated departments may be appointed as Supervisors, as well as any lecturers from the University of Verona whose area of interest is included in the Scientific-disciplinary Sectors (SSD) ING/INF/05 and INF/01. In addition to those who have the above requirements to be appointed as Supervisor, the following individuals may be appointed as co-supervisors: researchers working in external research institutes, research grant holders, post-doctoral fellowship holders, PhD students, technical staff of the Department, external experts appointed by an Italian University, corporate officers who have a remarkable experience in the field relevant to the topic of the dissertation. Examiners may be appointed among professors of the University of Verona, working in the Scientific- disciplinary Sectors (SSD) included in the educational offer of the Master’s degree programme in Medical Bioinformatics, and experts in the specific field of the dissertation topic.

Procedures and deadlines
The student who is about to complete their studies must identify a dissertation topic, proposed or approved by a Supervisor or co-supervisor/s (if any). When the work is nearing completion, the student must submit to the Teaching and Student Services Unit the graduation application, which must contain the title of the dissertation (even provisional), the name of the Supervisor, co-supervisor/s (only for external dissertations) and Examiner. Subsequently, on dates established by the Teaching and Student Services Unit, and in any case no later than 20 days before the graduation, the student must submit the graduation application form with the final title of the dissertation, which must be signed by the Supervisor. These documents must be delivered in accordance with the terms established by the Teaching and Student Services Unit.

The student will need to:

  • i) upload a copy of their dissertation on ESSE3;
  • ii) send a copy of their dissertation in PDF format to their Examiner.

In order to be admitted to the final examination, the student must have acquired the CFU in the SSD (Scientific-Disciplinary Sectors) set out in the Master’s degree regulations and teaching plan, and be up to date with the payment of their tuition fees. The Teaching and Student Services Unit of the Master's degree programme will invite all the Supervisors and co-supervisors involved, providing them with information about the date and time of the final examination.

Graduation Committee
The Graduation Committee shall include five members, of which at least four are professors in the Master's degree programme in Medical Bioinformatics. Based on the number of graduates, the Computer Science Teaching Committee will identify the most appropriate organisational methods for administering the examination, and it shall make available the calendar of tests at least one week before the examination itself. The procedures and deadlines for the submission of the graduation application are established by the Computer Science Teaching Committee and by the relevant offices.


Erasmus+ and other experiences abroad


Attendance

As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.


Career management


Student login and resources