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, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2021 Feb 26, 2021
Sessione estiva d'esame Jun 14, 2021 Jul 30, 2021
Sessione autunnale d'esame Sep 1, 2021 Sep 30, 2021
Degree sessions
Session From To
Sessione Estiva Jul 15, 2021 Jul 15, 2021
Sessione Autunnale Oct 15, 2021 Oct 15, 2021
Sessione Invernale Mar 15, 2022 Mar 15, 2022
Holidays
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 2021
Epifania Jan 6, 2021 Jan 6, 2021
Vacanze Pasquali Apr 2, 2021 Apr 5, 2021
Festa del Santo Patrono May 21, 2021 May 21, 2021

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

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

Baruffi Maria Caterina

symbol email mariacaterina.baruffi@univr.it

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

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

Cozza Vittoria

symbol email vittoria.cozza@univr.it

Daducci Alessandro

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

Delledonne Massimo

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

Franco Giuditta

symbol email giuditta.franco@univr.it symbol phone-number +39 045 802 7045

Fummi Franco

symbol email franco.fummi@univr.it symbol phone-number 045 802 7994

Giacobazzi Roberto

symbol email roberto.giacobazzi@univr.it symbol phone-number +39 045 802 7995

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

Spoto Nicola Fausto

symbol email fausto.spoto@univr.it symbol phone-number +39 045 8027940

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. 2021/2022
ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
English b2 level
4
F
-
Between the years: 1°- 2°
Other activities
2
F
-
Between the years: 1°- 2°

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

4S004548

Credits

12

Coordinatore

Rosalba Giugno

Language

English en

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

The teaching is organized as follows:

Laboratorio

Credits

6

Period

I semestre, II semestre

Academic staff

Rosalba Giugno

Teoria

Credits

6

Period

I semestre, II semestre

Academic staff

Rosalba Giugno

Learning outcomes

Knowledge and understanding The course aims to provide students with the knowledge and understanding of the paradigms and advanced programming tools for the management of biomedical / bioinformatic data and information. Applying knowledge and understanding The student will therefore be able to a) apply the paradigms and advanced programming tools for the analysis of genomic, transcriptomics and proteomics data; b) apply the code performance analysis and identify critical issues and their optimization. Making judgements Ability to independently propose effective and efficient solutions for the biomedical and bioinformatics application domain; ability to identify critical issues for the treatment of complex bioinformatics problems. Communication The student will also be able to interact with various interlocutors in a multidisciplinary biomedical and bioinformatics context, to interact with colleagues in the performance of group work, and to interact with the interlocutors in the working or research environment. Lifelong learning skills Ability to understand scientific literature in the process of interpreting the results or proposed solution, and to carry out individual and group in-depth studies aimed at tackling problems from the research and business world.

Program

R Programming
Overview and History of R
Workspace and Files
Objects and Data Structures
Missing Values
Sequence of Numbers
Subsetting
Split-Apply-Combine Funtions
Simulation
Reading Tabular Data
Logic
Control Structures
I/O operations
Functions
Base Graphics
Advanced Graphics

Bash- Scripting language
Overview of scripting language
Varables
Indexed arrays
Associative arrays
Conditional statements and operators
Comparison operators
Loops
I/O from files
Functions

R for Bioinformatics
Overview of BioConductor
Basic BioConductor Data Structures: IRanges and GenomicRanges
Classes and functions for representing biological strings: Biostrings
Classes and functions for representing genomes: BSgenome, GenomicRanges,
Annotation functions and overview of annotation web tools

RNA-SEQ Data Analysis using R/Python and web tools
Introduction to NGS technologies and experimental design
Data Pre-processing, from Fastq to BAM
Indexing Reference Genome
Mapping reads to a reference genome
Sorting and indexing alignment
Map quality control
Variant Discovery and Call set Refinement
Differential Analysis
Limma, Glimma, EdgeR
DESeq2
Practice on coding RNA and ncRNA detection and analysis


Applied Statistics for High-Throughput Data Mining
Introduction to variables and distribution
Linear modeling
Linear and generalized linear modeling
Model matrix and model formulae
Analysis of categorical variables, exploratory data analysis, multiple testing
Unsupervised analysis
Distance in high dimensions
Principal components analysis and multidimensional scaling
Unsupervised clustering
Partition Methods
Hierchical Methods
Density based methods
Batch effects

Advanced Analyses of biological data in R: methods for graphs and networks.
Networks in igraph
Create networks
Edge, vertex, and network attributes
Specific graphs and graph models
Reading network data from files
Turning networks into igraph objects
Plotting networks with igraph
Network and node descriptives
Distances and paths
Subgroups and communities
Assortativity and Homophily
Reconstruction and analysis of co-regulatory and co-espressed networks

The course includes special seminars in advanced topics such as Computational methods for the analysis of single cell data, graph mining, and multilayer networks. Topics are defined each year in base of the current trends in medical bioinformatics research. Students will have the possibility to use software related to the chosen topics and analyze real cases.

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Laboratorio Roger D. Peng Exploratory Data Analysis with R https://leanpub.com/exdata 2016
Teoria Roger D. Peng Exploratory Data Analysis with R https://leanpub.com/exdata 2016
Teoria Michael I. Love, Simon Anders, Vladislav Kim, Wolfgang Huber RNA-Seq workflow: gene-level exploratory analysis and differential expression https://f1000research.com/articles/4-1070/v1 2015

Examination Methods

The exam consists of a written part (A) and the development of a project (B). (A) consists in developing during the test day a R program for solving a given problem using genomic, transcriptomic or proteomic data. (B) is the development of a project agreed upon with the teacher after request by email and appointment for the elaboration of the specifications (the project is valid throughout the academic year). The projects have different levels of difficulty. Every difficulty corresponds to a maximum evaluation value.

Voting for parts A and B is expressed in thirty.

The final vote is calculated as min (31, ((A + B) / 2) + C).
C is expressed in the interval [-4, + 4] and reflects the maturation and scientific autonomy acquired during the development of the tests and the project, in the exposure and in the interpretation of the scientific literature and the scientific context of the project.

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Type D and Type F activities

I semestre From 10/1/20 To 1/29/21
years Modules TAF Teacher
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
II semestre From 3/1/21 To 6/11/21
years Modules TAF Teacher
1° 2° Introduction to 3D printing D Franco Fummi (Coordinatore)
1° 2° Python programming language D Vittoria Cozza (Coordinatore)
1° 2° HW components design on FPGA D Franco Fummi (Coordinatore)
1° 2° Rapid prototyping on Arduino D Franco Fummi (Coordinatore)
1° 2° Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
1° 2° The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Nicola Fausto Spoto (Coordinatore)

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.


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