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. 2018/2019

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

simone.accordini@univr.it +39 045 8027657

Belussi Alberto

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

Bicego Manuele

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

Bombieri Cristina

cristina.bombieri@univr.it 045-8027209

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

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

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 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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S004548

Credits

12

Coordinatore

Rosalba Giugno

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

English

The teaching is organized as follows:

Teoria

Credits

6

Period

II semestre, I semestre

Academic staff

Rosalba Giugno

Laboratorio

Credits

6

Period

II semestre, I 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.

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.

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
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
Teoria Kolaczyk, Eric D., Csárdi, Gábor Statistical Analysis of Network Data with R Springer 2014
Laboratorio Roger D. Peng Exploratory Data Analysis with R https://leanpub.com/exdata 2016
Laboratorio 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
Laboratorio Kolaczyk, Eric D., Csárdi, Gábor Statistical Analysis of Network Data with R Springer 2014

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.

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.