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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
| Period | From | To |
|---|---|---|
| I sem. | Oct 2, 2017 | Jan 31, 2018 |
| II sem. | Mar 1, 2018 | Jun 15, 2018 |
| Session | From | To |
|---|---|---|
| Sessione invernale d'esami | Feb 1, 2018 | Feb 28, 2018 |
| Sessione estiva d'esame | Jun 18, 2018 | Jul 31, 2018 |
| Sessione autunnale d'esame | Sep 3, 2018 | Sep 28, 2018 |
| Session | From | To |
|---|---|---|
| Sessione Estiva Lauree Magistrali | Jul 19, 2018 | Jul 19, 2018 |
| Sessione Autunnale Lauree Magistrali | Oct 18, 2018 | Oct 18, 2018 |
| Sessione Invernale Lauree Magistrali | Mar 21, 2019 | Mar 21, 2019 |
| Period | From | To |
|---|---|---|
| Christmas break | Dec 22, 2017 | Jan 7, 2018 |
| Easter break | Mar 30, 2018 | Apr 3, 2018 |
| Patron Saint Day | May 21, 2018 | May 21, 2018 |
| Vacanze estive | Aug 6, 2018 | Aug 19, 2018 |
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.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
Bloisi Domenico Daniele
domenico.bloisi@univr.it
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.
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| Modules | Credits | TAF | SSD |
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1° Year
| Modules | Credits | TAF | SSD |
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2° Year
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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.
Programming laboratory for bioinformatics (2017/2018)
Teaching code
4S004548
Teacher
Coordinatore
Credits
12
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
II sem., I sem.
Learning outcomes
The course aims to provide the programming and interpretation tools necessary for the analysis of genomic, transcriptional and proteomic data from the latest generation technologies. For each subject, theoretical lessons are given followed by practices in laboratory.
At the completion of the course the students will be able to program, according to the data to be analyzed and the biomedical question to solve, the appropriate analysis pipeline. They will also be able to interpret the obtained results.
Program
Programming in R. Introduction. Data Structures: Vectors, Matrices, Lines, Data Frame. Data Frame. Functions. In / Out. Visualization, the grammar of graphics and ggplot2.
Statistics: median, MAD, rank test, Spearman, robust linear mode, multiple testing, linear models,
Program with Bioconductor. Structure, principles and function. Sequence alignment and aligners, Experimental design, batch effects and confounding, RNA-Seq data analysis and differential expression, Methylation analysis, CNV analysis, Microarray analysis. Annotation resources, Gene set enrichment analysis.
Introduction and Basics of Programming in Python and Bash.
Advanced analysis algorithms: Clustering and classification, resampling: cross-validation, bootstrap, and permutation tests, biological network analysis.
Didactic material (Mainly based on continuously updated scientific articles and online programming guides) is available in the course e-learning platform of the University.
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| Rafael A Irizarry and Michael I Love | Data Analysis for the Life Sciences | https://leanpub.com/dataanalysisforthelifesciences/ | 2015 |
Examination Methods
The exam consists of a written part (A) and the development of a project (B). A consists in developing 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. Students will hold an interview to comment the A and B parts.
Concerning point A, attendants at the course have the right to participate in two intermediate trials scheduled during the year. The tests consist of the development of an R program for biomedical data analysis. The two tests will have a cumulative vote expressed in thirty and it will be communicated to the students at the end of the course.
Concerning point B, attendees at the course will be able to expose to the class their project, the research context in which the project is located, and the state of progress of the course.
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.
Bibliography
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.
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.
Graduation
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.
