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.

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 Bioinformatica - 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.

2° Year  activated in the A.Y. 2010/2011

ModulesCreditsTAFSSD
12
B
INF/01
12
C
BIO/10
6
C
BIO/18
activated in the A.Y. 2010/2011
ModulesCreditsTAFSSD
12
B
INF/01
12
C
BIO/10
6
C
BIO/18

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S01908

Coordinator

Giuditta Franco

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Period

I semestre dal Oct 3, 2011 al Jan 31, 2012.

Learning outcomes

The course is designed to introduce several methodologies to model phenomena occurring in nature, by means of discrete mathematical tools and computational systems. The goal is to develop the ability of the student to master different approaches of discrete biological modeling, by means of the presentation of the state of the art and of the most recent problematics. Basic concepts (of mathematics, computer science, biology) are recalled, to better understand both traditional mathematical models and computational models of cellular and molecular processes, proposed along with a few case studies.

Program

Part I (traditional mathematical models)
Introduction to different classes of models, and to discrete models
Discrete mathematics fundamentals - induction and recurrence
Fibonacci numbers and golden section in nature
Iterative biological models
Malthusian biological population growth models
Dynamical systems, and logistic map
Lotka-Volterra model and cobweb model of supply/demand interaction
Discrete SIR model of epidemics

Part II (non-conventional bioinformatics models)
Formal languages and biological grammars
Computational models of bio-molecular processes, NP-completeness
Informational structure of DNA molecule, operations, experimental techniques, and bio-algorithms
XPCR for string recombination and concatenation
DNA algorithms solving SAT
Membrane models, and minimal cell
Discrete models of metabolism
Procedures based on bacterial growth, and related experimental techniques

Examination Methods

Oral exam, or a couple of written midterm exams

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

Teaching materials e documents