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
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 2025/2026The 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
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2° Year activated in the A.Y. 2021/2022
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1 module among the following3° Year activated in the A.Y. 2022/2023
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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.
Discrete Biological Models (2022/2023)
Teaching code
4S01908
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Teoria
Discrete biological models
Learning objectives
The aim of the course is to present methods from discrete mathematics which are employed in the analysis of biological phenomena, with a major emphasis on the computational analysis of genomes. At the end of the course the students will be able to apply discrete probability and information theoretic tools for analysing genomic data.
Prerequisites and basic notions
Linear algebra, Informational methods (discrete mathematics, combinatorics)
Program
In this course we will introduce discrete models for attacking some computational problems arising in biological research: We will see how combinatorial structures can be applied to computational biology problems. In particular, we will study:
- strings for modelling DNA, RNA, and proteins
- graphs for modelling molecules
- graphs for modelling interactions between proteins (protein interaction networks)
- discrete functions (e.g. temporal series) for describing dynamics in biology
- human genomic variation, modelled with strings and with graphs
- haplotyping, modelled with strings and with matrices
- genome rearrangements, modelled with permutations and with strings
- DNA sequencing (layouts, grpahs)
- physical map of DNA (multisets, graphs)
- mass spectrometry data (strings)
- Fibonacci sequence
- malthusian models of population growth
- criteria for solving linear recurrences
- dynamic study of the logistic map
- metabolic dynamics modelled with graphs (metabolic networks)
Bibliography
Didactic methods
lectures and exercise sessions
Learning assessment procedures
Written exam, possibly followed by an oral exam: students who reach a grade of over 25 in the written exam have to take an additional oral exam, for the others the oral is optional. The written exam consists of practical applications (exercises) as well as theoretical questions (problems studied, mathematical properties, which models exist etc.). In the oral exam, the student will explain in detail their solutions in the written exam, and show to what extent they have mastered the topics.
Exam language
italiano
