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.

Study Plan

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea in Matematica applicata - Enrollment from 2025/2026

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.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
12
A
MAT/02 ,MAT/03
12
A
MAT/05
12
A
FIS/01
12
A
INF/01
6
A
MAT/08
6
B
MAT/01

2° Year   activated in the A.Y. 2020/2021

ModulesCreditsTAFSSD
12
B
MAT/05
6
B
MAT/03
6
B
MAT/08
6
A
MAT/02
6
B
MAT/05
6
C
SECS-P/01
6
C
SECS-P/01
9
B
MAT/06
English B1
6
E
-

3° Year   activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
6
C
SECS-P/05
9
C
SECS-S/06
Final exam
6
E
-
activated in the A.Y. 2020/2021
ModulesCreditsTAFSSD
12
B
MAT/05
6
B
MAT/03
6
B
MAT/08
6
A
MAT/02
6
B
MAT/05
6
C
SECS-P/01
6
C
SECS-P/01
9
B
MAT/06
English B1
6
E
-
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
6
C
SECS-P/05
9
C
SECS-S/06
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
12
D
-
Between the years: 1°- 2°- 3°
Other activitites
6
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.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Mathematical and Statistical Methods in Biology  (2021/2022)

Teaching code

4S004794

Academic staff

Giacomo Albi, Roberto Chignola

Coordinator

Giacomo Albi

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/13 - EXPERIMENTAL BIOLOGY

Period

Primo semestre dal Oct 4, 2021 al Jan 28, 2022.

Lessons timetable MoodleMoodle Seminars 0

Learning outcomes

This course is an introduction to the most common mathematical models developed to solve biology and medicine problems. Deterministic and probabilistic models, and the main statistical approaches used to take into account the uncertainties that characterize complex biological systems will be discussed. At the end of the course students should be able to: - understand and critically discuss the main models of biological systems with particular reference to the validity of the assumptions and the definition of appropriate parameters; - develop and analyze simple models; - understand the effects of the parameters also in relation to the unavoidable uncertainty of their estimate; - compare the predictions of the models with the experimental data; - communicate the results in a multidisciplinary context

Program

The entire course will be available online. Part I (Albi) - Single specie model: Malthus, Birth-Death, Logistic growth. - Multi-species model: Predator-Prey, competition and cooperation. - Epidemiological model: SIR, SEIR and age structured - Time delay models - PDE models of reaction and diffusion. - Parameter identification for differential model - 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 - statistical inference - main statistical methods used in biomedicine with univariate and multivariate variables - introduction to the R environment for scientific calculus and statistics

Bibliography

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Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

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. Students will be required to present a short essay on a bio-mathematical topic that they will choose by searching the scientific literature. Emphasis will be given to the students' ability to analyze and critically revise the selected problem. Students will be also required to reproduce and eventually extend all the mathematical aspects using the software MatLab or R.

The assessment methods could change according to the academic rules.
The online exam is granted for all the students will require it during the academic year 2020/21.

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