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

Queste informazioni sono destinate esclusivamente agli studenti e alle studentesse già iscritti a questo corso.
Se sei un nuovo studente interessato all'immatricolazione, trovi le informazioni sul percorso di studi alla pagina del corso:

Laurea in Matematica applicata - Immatricolazione dal 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
6
B
MAT/08
12
A
FIS/01
6
B
MAT/01
12
A
INF/01

2° Year   activated in the A.Y. 2017/2018

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

3° Year   activated in the A.Y. 2018/2019

ModulesCreditsTAFSSD
6
C
SECS-P/05
12
C
SECS-S/06
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
6
E
-
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
12
B
MAT/05
6
B
MAT/08
6
A
MAT/02
6
B
MAT/03
6
C
SECS-P/01
6
C
SECS-P/01
6
B
MAT/06
6
B
MAT/05
6
E
-
activated in the A.Y. 2018/2019
ModulesCreditsTAFSSD
6
C
SECS-P/05
12
C
SECS-S/06
6
B
MAT/08
6
B
MAT/09
6
B
MAT/06
6
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
12
D
-
Between the years: 1°- 2°- 3°
Altre attività formative
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 (2018/2019)

Teaching code

4S004794

Credits

6

Coordinator

Giacomo Albi

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/13 - EXPERIMENTAL BIOLOGY

MoodleMoodle Seminars 0

The teaching is organized as follows:

Parte 2

Credits

3

Period

I semestre

Academic staff

Roberto Chignola

Lessons timetable
Parte 1

Credits

3

Period

I semestre

Academic staff

Giacomo Albi

Lessons timetable

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 model of single population:
* Growth models
* Time delay models
* Biological systems with feedback
B) Discrete, and continuous model of interacting populations
* Linear and non-linear models: Predator-Prey models; SIS, SIR models, tumor growth.
* Single perturbed systems & oscillators: Enzyme Kinetics, Fitzhugh–Nagumo Model for neuronal membrane,
synchronization models.
C) Discrete and continuous probabilistic models:
* Stochastic growth models, and stochastic predator-prey models, oscillators with random noise.
* Reaction-Diffusion processes, Chemotaxis.
* Monte-Carlo methods
D) Parameter identification and data analysis
* Statistical inference, theory of the estimators, maximum likelihood, test of hypothesis.
* Data fitting, Linear and non-linear regression, Kalmann filter, sensitivity analysis.

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



Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Parte 1 J. Murray Mathematical Biology Springer 2002 0-387-95223-3
Parte 1 J. D. Logan, W. R. Wolesensky Mathematical Methods in Biology 2009 9780470525876
Parte 1 Brian Ingalls Mathematical Modelling in Systems Biology: An Introduction  
Parte 1 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. Possibility of midterm examination.

Part B: Oral evaluation. The students will have to prepare and critically discuss a short essay.

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