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.

Teaching code

4S00995

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).

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