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 - II semestre | Oct 2, 2017 | Jun 15, 2018 |
| 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 di laurea estiva | Jul 23, 2018 | Jul 23, 2018 |
| Sessione di laurea autunnale | Oct 17, 2018 | Oct 17, 2018 |
| Sessione autunnale di laurea | Nov 23, 2018 | Nov 23, 2018 |
| Sessione di laurea invernale | Mar 22, 2019 | Mar 22, 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 Enrollment FAQs
Academic staff
alberto.benvegnu@univr.it
leonardpeter.bos@univr.it
maurizio.boscaini@univr.it
federico.busato@univr.it
Magazzini Laura
laura.magazzini@univr.it
045 8028525
gino.mariotto@univr.it
simone.zuccher@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 enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
2° Year activated in the A.Y. 2018/2019
| Modules | Credits | TAF | SSD |
|---|
3° Year activated in the A.Y. 2019/2020
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
|---|
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.
Mathematical and Statistical Methods in Biology (2019/2020)
Teaching code
4S004794
Academic staff
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
BIO/13 - EXPERIMENTAL BIOLOGY
Period
I semestre dal Oct 1, 2019 al Jan 31, 2020.
Learning outcomes
The course is an introduction to the basic and most known mathematical models developed to solve biological and medical problems.
We will discuss deterministic as well as probabilistic models, together with the statistical tools used to quantify the uncertainties characterizing complex biological systems.
At the end of the course the students should be able to :
- understand and discuss the main models of biological systems, with particular attention to the validity of the assumptions, and the definition of different parameters;
- develop and analyze simple models;
- understand the impact of the parameter, also with respect to their measure uncertainty;
- compare the predictions of the models with the experimental data;
- communicate the results in an interdisciplinary environment.
Program
Part I (Albi)
A) Discrete, and continuous models:
* Single specie model: Mathus, Birth-Death, Logistic growth.
* Multi-species model: Predator-Prey, SIS, SIR, tumoral growth.
* Time delay models, ingle perturbed systems & oscillators.
* Models with noise.
B) Parameter identification and data analysis
* Statistical inference, theory of the estimators, maximum likelihood, test of hypothesis.
* Data fitting, Linear and non-linear regression, parameter identification.
Examples and exercises in class with dedicated softwares (Matlab and/or R)
Part II (Chignola)
- probabilistic models for biomedicine
- the Luria and Delbrück experiment
- growth models for population biology
- allometry and scaling laws
- phenomenological models for tumor growth
- models for cell physiology
- multi-scale models in oncology
- Biological oscillations
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| N. F. Britton | Essential Mathematical Biology | Springer | 2003 | 978-1-4471-0049-2 | |
| M. Squassina, S. Zuccher | Introduzione all'Analisi Qualitativa delle Equazioni Differenziali Ordinarie. 332 pagine, 365 figure. | Apogeo Editore | 2008 | 9788850310845 | |
| J. Murray | Mathematical Biology | Springer | 2002 | 0-387-95223-3 | |
| Brian Ingalls | Mathematical Modelling in Systems Biology: An Introduction | ||||
| V. Comincioli | METODI NUMERICI E STATISTICI PER LE SCIENZE APPLICATE | Universitá degli Studi di Pavia | 2004 |
Examination Methods
Part A: written exam with the help of computer, solution of exercises on the basis of the one solved during the course. Students will be required to modify the numerical codes seen in Matlab/Octave/R. Possibility of midterm examination.
Part B: Oral evaluation. The students will have to prepare and critically discuss a short essay.
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 also via the Univr app.
Graduation
Documents
| Title | Info File |
|---|---|
1. Come scrivere una tesi
|
pdf, it, 31 KB, 29/07/21 |
|
2. How to write a thesis
|
pdf, it, 31 KB, 29/07/21 |
|
5. Regolamento tesi
|
pdf, it, 171 KB, 20/03/24 |
List of thesis proposals
| theses proposals | Research area |
|---|---|
| Formule di rappresentazione per gradienti generalizzati | Mathematics - Analysis |
| Formule di rappresentazione per gradienti generalizzati | Mathematics - Mathematics |
| Proposte Tesi A. Gnoatto | Various topics |
| Mathematics Bachelor and Master thesis titles | Various topics |
Attendance modes and venues
As stated in the Teaching Regulations , except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.
The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus.
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.
Career management
Student login and resources
Erasmus+ and other experiences abroad
Ongoing orientation for students
The committee has the task of guiding the students throughout their studies, guiding them in their choice of educational pathways, making them active participants in the educational process and helping to overcome any individual difficulties.
It is composed of professors Lidia Angeleri, Sisto Baldo, Marco Caliari, Paolo dai Pra, Francesca Mantese, and Nicola Sansonetto
To send an email to professors: name.surname@univr.it
