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.
Informational Methods (2021/2022)
Teaching code
4S00995
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
Primo semestre dal Oct 4, 2021 al Jan 28, 2022.
Learning outcomes
The course introduces the fundamental discrete structures by emphasizing their use in the definition of mathematical models of biological relevance. The students will acquire knowledge about the es-sentials of discrete mathematics; formal notions and methods for studying problems by means of computers; methods for representation of biological information; and they will be able to apply such knowledge to analyze biological data of different types (genomic sequences, biological processes, networks of biological interactions) by means of information theoretic concepts.
Program
Part1. Basics of set theory, combinatorics and discrete probability
Relations, equivalences; numerical systems; Fibonacci series (golden ratio, Binet's theorem and applications); recurrences and asyntotic analysis; multisets sequences, strings, and languages; discrete probability spaces, random variables, mean and variance;
Part 2. Basics of graph theory:
Directed and undirected Graphs and their representations; forests and trees; spanning trees; connectivity problems; structural induction on graphs.
Part3. Elements of computability (formal languages and automata):
Formal grammars and languages; patterns and regular expressions; finite state automata; Turing machines; decidability semidecidability and undecidability.
Part 4. Elements of Information Theory and compression
Information sources; information measures, entropy, mutual information and informational divergence; information theoretic similarity and dissimilarity measures; uniquely decodable codes and prefix codes; optimal codes; compression based sequence similarity.
Part 5. Discrete functions, dynamics and temporal series:
Metabolic processes; the epidemiological model SIR; geometric progression and Malthus model; population growth models (non linear); elements of dynamical systems
Examination Methods
The exam will be a written test including both open and multiple choice question. The test will verify that the student has reached a sufficent level of fluency in the topics studied and that they have acquired the ability to employ the techniques and the aanalytical tools presented in class also in new situations (contexts not explicitly treated in the course).
