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.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
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I semestre | Oct 1, 2018 | Jan 31, 2019 |
II semestre | Mar 4, 2019 | Jun 14, 2019 |
Session | From | To |
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Sessione invernale d'esame | Feb 1, 2019 | Feb 28, 2019 |
Sessione estiva d'esame | Jun 17, 2019 | Jul 31, 2019 |
Sessione autunnale d'esame | Sep 2, 2019 | Sep 30, 2019 |
Session | From | To |
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Sessione Estiva | Jul 18, 2019 | Jul 18, 2019 |
Sessione Autunnale | Oct 17, 2019 | Oct 17, 2019 |
Sessione Invernale | Mar 18, 2020 | Mar 18, 2020 |
Period | From | To |
---|---|---|
Festa di Ognissanti | Nov 1, 2018 | Nov 1, 2018 |
Sospensione dell'attività didattica | Nov 2, 2018 | Nov 3, 2018 |
Festa dell’Immacolata | Dec 8, 2018 | Dec 8, 2018 |
Vacanze di Natale | Dec 24, 2018 | Jan 6, 2019 |
Vacanze di Pasqua | Apr 19, 2019 | Apr 28, 2019 |
Festa della liberazione | Apr 25, 2019 | Apr 25, 2019 |
Festa del lavoro | May 1, 2019 | May 1, 2019 |
Festa del Santo Patrono | May 21, 2019 | May 21, 2019 |
Festa della Repubblica | Jun 2, 2019 | Jun 2, 2019 |
Vacanze estive | Aug 5, 2019 | Aug 18, 2019 |
Exam calendar
Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
Study Plan
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 enrolment year.
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1° Year
Modules | Credits | TAF | SSD |
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2° Year
Modules | Credits | TAF | SSD |
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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.
Natural Computing (2019/2020)
Teaching code
4S004557
Teacher
Coordinatore
Credits
6
Also offered in courses
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
I semestre dal Oct 1, 2019 al Jan 31, 2020.
Learning outcomes
Knowledge and understanding
The course is designed to first recall basic concepts of traditional computational models, such as formal languages and automata, and then present several models of bio-inspired computing, including bio-molecular algorithms. Main models of natural computing are presented, in terms of computational processes observed in and inspired by nature.
Applying knowledge and understanding
During the course students will aquire the following competences:
Applying basic notions of discrete mathematics (sets, multisets, sequences, trees, graphs, induction, grammars and finite automata) to explain a few computational methods both to process genomic information and to investigate metabolic networks.
Making judgements
Students will develop the required skills in order to be autonomous in the following tasks:
- choose and processing data in large genomic contexts;
- choose the appropriate methodologies and tools for represent biological information in the context of discrete biological models.
Communication skills
The student will learn how to address the correct and appropriate methods and languages for communicating
problems and solutions in the field of computationaql genomics and of biological dynamics. The course aims at developing the ability of the student both to master notions of discrete structures and dynamics, and to deepen his/her notion of Turing computation, in order to extend it to informational processes involving either natural or bio-inspired algorithms. Student's knowledge of all the topics explained in class will be tested at the exam, along with his/her learning and understanding skills.
Lifelong learning skills
Introduction to natural computing, biological algorithms, and life algorithmic strategies.
Basic notions of discrete mathematics and of formal language theory (Chomsky's hierarchy, automata, and computability).
Elements of information theory (information sources, codes, entropy, and entropy divergences, typical sequences, first and second Shannon's theory).
Methods to extract and analyze genomic dictionaries.
Genomic profiles and distributions of recurrent motifs.
Software IGtools to analyze and visualize genomic data.
Computational models of bio-molecular processes, such as DNA self-assembly and membrane computing.
DNA computing and bio-complexity of bio-algorithms.
DNA algorithms to solve NP-complete problems.
MP grammars, networks, and metabolic dynamics.
Program
Introduction to natural computing, life algorithmic strategies, biological algorithms and paradoxes.
DNA computing on double strings, and computational complexity of bio-algorithms
DNA algorithms to solve a couple of NP-complete problems, to extract and generate DNA libraries Methods to extract and analyze genomic dictionaries
Genomic profiles and distributions of recurrent motifs
Software IGtools to analyze and visualize genomic data
Discrete representation of biochemical systems
Metabolic grammars, networks, and related (inverse) dynamics
Computational models for biomolecular and metabolic processes:
Basic data structures to represent chemical reactions, membrane hierarchies, biological interactions
Formal languages and grammars, Chomsky hierarchy
Specific characterization of REG, REC, CF classes
Finite state automata, Turing machines, computational universality and (bio)complexity
A nutshell of information theory.
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
Gheorghe Paun, Grzegorz Rozenberg, Arto Salomaa | DNA computing: new computing paradigms (Edizione 3) | Springer | 2013 | ||
Alexander Meduna | Formal Languages and Computation: Models and Their Applications | Auerbach Publications | 2014 | ||
Vincenzo Manca | Infobiotics | Springer | 2013 |
Examination Methods
Only for the first exam session (by February), work assignments (e.g. on topics of computational genomics) or seminars (on recent scientic articles) will be proposed for students who want to improve their performance in the written exam. Afterwards, in all other exam sessions, only oral exams will be allowed.
Bibliography
Type D and Type F activities
Modules not yet included
Career prospects
Module/Programme news
News for students
There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.
Further services
I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.
Graduation
Attendance
As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.Please refer to the Crisis Unit's latest updates for the mode of teaching.