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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Semester 1 | Oct 1, 2024 | Jan 31, 2025 |
Semester 2 | Mar 3, 2025 | Jun 13, 2025 |
Session | From | To |
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Winter exam session | Feb 3, 2025 | Feb 28, 2025 |
Summer exam session | Jun 16, 2025 | Jul 31, 2025 |
Autumn exam session | Sep 1, 2025 | Sep 30, 2025 |
Session | From | To |
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Sessione di laurea estiva | Jul 17, 2025 | Jul 17, 2025 |
Sessione di laurea autunnale | Oct 21, 2025 | Oct 21, 2025 |
Period | From | To |
---|---|---|
Tutti i Santi | Nov 1, 2024 | Nov 1, 2024 |
Festa dell'Immacolata | Dec 8, 2024 | Dec 8, 2024 |
Vacanze di Natale | Dec 23, 2024 | Jan 6, 2025 |
Vacanze di Pasqua | Apr 18, 2025 | Apr 21, 2025 |
Festa della Liberazione | Apr 25, 2025 | Apr 25, 2025 |
Festa del Lavoro | May 1, 2025 | May 1, 2025 |
Festa del Santo Patrono | May 21, 2025 | May 21, 2025 |
Festa della Repubblica | Jun 2, 2025 | Jun 2, 2025 |
Vacanze estive | Aug 11, 2025 | Aug 16, 2025 |
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.
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 enrollment year.
1° Year
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2° Year It will be activated in the A.Y. 2025/2026
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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.
Machine learning for biological structures and networks (2024/2025)
Teaching code
4S009831
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Courses Single
Authorized
The teaching is organized as follows:
Teoria
Laboratorio
Learning objectives
The course is aimed at providing the theoretical and applicative basis of Pattern Recognition techniques for the computational analysis of biological objects with a complex structure (such as graphs, sequences, networks, strings and so on). In particular, the course introduces and discusses the most important computational techniques for the analysis of structured data, with particular emphasis on the representation and on the generative and discriminative approaches. Knowledge and understanding: At the end of the course, the student has to demonstrate to be able to apply to real data the methodologies for recognition of complex data, by developing a Pattern Recognition system. Applying knowledge and understanding: a) Representation of biological data with complex structure b) Classification of biological data with complex structure c) Clustering of biological data with complex structure Making judgements: At the end of the course, the student should demonstrate to be able to propose in an autonomous way efficient solutions for a given biomedical and bioinformatics domain, being able to identify critical issues linked to complex bioinformatics problems. Communication: At the end of the course, the tudent should demonstrate to be able to interact with colleagues in work groups. Lifelong learning skills: At the end of the course, the student should demonstrate to be able to learn and autonomously apply novel methodologies for facing bioinformatics and clinical problems. In particular, the student should demonstrate to be able to analyse a biological problem, involving complex and structured biological data, from a Pattern Recognition perspective; he will also have the skills needed to study, invent, develop and implement the different components of a Pattern Recognition System for biological structured data. The student will also be able to autonomously proceed with further Pattern Recognition studies.
Prerequisites and basic notions
Theory: basic notions on Pattern Recognition (a brief recap will be given at the beginning of the course), Basic notions of Algorithms, Probability, Statistics, Algebra.
Lab: Programming skills, Programming language used: Matlab (there will be an introductory lecture for students who are not familiar with Matlab)
Program
CHAPTER 1 Basic Pattern Recognition concepts and introduction to structured data
CHAPTER 2. Representation of structured data
- The Bag of words representation
- The dissimilarity-based representation
- Dimensionality reduction
- Learning representation with Neural Networks
CHAPTER 3. Models for structured data
- Generative models
- Bayes Networks
- Learning and inference
CHAPTER 4. Kernels for structured data
- Support Vector Machines e kernel
- Kernels for structured data
CHAPTER 5. Advances Learning paradigms
The course also contains a lab part, where algorithms seen during the theory part will be implemented and deeply analysed
Bibliography
Didactic methods
In person lectures plus in person lab sessions
Learning assessment procedures
The exam is aimed at the verification of the following skills:
- capability of clearly and concisely describe the different components of a Pattern Recognition System for structured data
- capability of analise, understand and describe a Pattern Recognition system (or a given part of it) relative to a biological problem which involves structured data
The exam consists of two parts
i) a written exam containing questions on topics presented during the course plus an exercise of "code understanding", for the lab part (15 points available). The written part is passed is the grade is greater or equal to 9.
ii) an oral presentation of a scientific paper published in relevant bioinformatics journals or conferences on a given argument (decided during the course). The paper is chosen by the candidate and approved by the instructor (15 points available).
The two parts of the exam can be passed separately; every part is passed if the grade is larger or equal to 9. The total exam is passed when both parts are passed: the final grade is the sum of the two grades. The evaluation of each part is maintained valid for the whole academic year.
Evaluation criteria
For the written part:
- Understanding of the questions and knowledge of related theoretical topic
- Clarity and precision of the used language
For the oral part:
- capability of choosing a scientific paper which is relevant with respect to the assigned topic
- Capability of understanding the methodologies and the results presented in the paper
- Capabilitiy of summarizing the paper in a conference-like talk
- Capability of rasining the interest of participants and clarity of exposition
Criteria for the composition of the final grade
The final grade is the sum of the two grades.
Exam language
English
Sustainable Development Goals - SDGs
This initiative contributes to the achievement of the Sustainable Development Goals of the UN Agenda 2030. More information on sustainabilityType D and Type F activities
Type D learning activities are the student's choice, type F activities are additional knowledge useful for job placement (internships, transversal skills, project works, etc.). According to the Teaching Regulations of the Course, some activities can be chosen and entered independently in the booklet, others must be approved by a special committee to verify their consistency with the study plan. Type D or F learning activities can be covered by the following activities.
1. Modules taught at the University of Verona
Include the modules listed below and/or in the Course Catalogue (which can also be filtered by language of delivery via Advanced Search).
Booklet entry mode: if the teaching is included among those listed below, the student can enter it independently during the period in which the curriculum is open; otherwise, the student must make a request to the Secretariat, sending the form to carriere.scienze@ateneo.univr.it during the period indicated.
2. CLA certificate or language equivalency
In addition to those required by the curriculum/study plan, the following are recognized for those matriculated from A.Y. 2021/2022:
- English language: 3 CFUs are recognized for each level of proficiency above that required by the course of study (if not already recognized in the previous course of study).
- Other languages and Italian for foreigners: 3 CFUs are recognized for each proficiency level starting from A2 (if not already recognized in the previous study cycle).
These CFUs will be recognized, up to a maximum of 6 CFUs in total, of type F if the study plan allows it, or of type D. Additional elective credits for language knowledge may be recognized only if consistent with the student's educational project and if adequately justified.
Those enrolled until A.Y. 2020/2021 should consult the information found here.
Method of inclusion in the booklet: request the certificate or equivalency from CLA and send it to the Student Secretariat - Careers for the inclusion of the exam in the career, by email: carriere.scienze@ateneo.univr.it
3. Transversal skills
Discover the training paths promoted by the University's TALC - Teaching and learning center intended for students regularly enrolled in the academic year of course delivery https://talc.univr.it/it/competenze-trasversali
Mode of inclusion in the booklet: the teaching is not expected to be included in the curriculum. Only upon obtaining the Open Badge will the booklet CFUs be automatically validated. The registration of CFUs in career is not instantaneous, but there will be some technical time to wait.
4. Contamination lab
The Contamination Lab Verona (CLab Verona) is an experiential course with modules on innovation and enterprise culture that offers the opportunity to work in teams with students from all areas to solve challenges set by companies and organisations.
Upon completion of a CLab, students will be entitled to receive 6 CFU (D- or F-type credits).
Find out more: https://www.univr.it/clabverona
PLEASE NOTE: In order to be admitted to any teaching activities, including those of your choice, you must be enrolled in the academic year in which the activities in question are offered. Students who are about to graduate in the December and April sessions are therefore advised NOT to undertake extracurricular activities in the new academic year in which they are not enrolled, as these graduation sessions are valid for students enrolled in the previous academic year. Therefore, students who undertake an activity in an academic year in which they are not enrolled will not be granted CFU credits.
5. Internship/internship period
In addition to the CFUs stipulated in the curriculum/study plan (check carefully what is indicated on the Teaching Regulations) here you can find information on how to activate the internship.
Check in the regulations which activities can be Type D and which can be Type F.
Please also note that for traineeships activated after 1 October 2024, it will be possible to recognise excess hours in terms of type D credits, limited only to traineeship experiences carried out at host organisations outside the University.
years | Modules | TAF | Teacher |
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1° 2° | Attention Laboratory | D | Not yet assigned |
1° 2° | Elements of Cosmology and General Relativity | D | Not yet assigned |
1° 2° | Introduction to quantum mechanics for quantum computing | D | Not yet assigned |
1° 2° | Introduction to smart contract programming for ethereum | D | Not yet assigned |
1° 2° | BEYOND ARDUINO: FROM PROTOTYPE TO PRODUCT WITH STM MICROCONTROLLER | D | Not yet assigned |
1° 2° | APP REACT PLANNING | D | Not yet assigned |
1° 2° | HW components design on FPGA | D | Not yet assigned |
years | Modules | TAF | Teacher |
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1° 2° | Attention Laboratory | D | Not yet assigned |
1° 2° | LaTeX Language | D | Not yet assigned |
1° 2° | Python programming language | D | Not yet assigned |
1° 2° | Rapid prototyping on Arduino | D | Not yet assigned |
1° 2° | Programming Challanges | D | Not yet assigned |
1° 2° | Protection of intangible assets (SW and invention)between industrial law and copyright | D | Not yet assigned |
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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
Deadlines and administrative fulfilments
For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.
Need to activate a thesis internship
For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.
Final examination regulations
Upon completion of the Master’s degree dissertation, students are awarded 24 CFU, which equates to no more than 4-5 months of full-time work. The dissertation may be written and presented in English or Italian, also using multimedia tools such as presentations and videos.
Goals
The primary goal of a dissertation is to develop an original study that may include an application project or a theoretical topic related to specific design issues, or a critical review of the most recent developments in a given field of study. During the preparation of the dissertation, under the guidance of the Supervisor and co-supervisors (if any), the student is expected to conduct an in-depth study of the chosen topic, while gaining the ability to summarise and creatively apply the knowledge acquired. The dissertation should focus on topics of bioinformatics and medical informatics, or closely related areas of study. The work shall consist in the written presentation of activities that may be structured as follows:
- design and development of applications or systems;
- critical analysis of contributions from the scientific literature;
- original research contributions.
The dissertation may be written either in English or in Italian, and can be presented either in English or in Italian, also relying on multimedia tools such as presentations and videos. Should the dissertation be written in Italian, the work will need to include an abstract in English.
Assessment methods and examination procedures
The final examination consists in writing a Master’s degree dissertation, which will engage the student in a work of research, formalisation, design or development, thus contributing to complete their technical and scientific training. Each dissertation can be either internal or external, depending on whether it is carried out at the University of Verona or in collaboration with another institution. For each dissertation a Supervisor, one or more co-supervisors (optional) and an Examiner will be appointed. The Examiner is appointed by the Computer Science Teaching Committee at least 20 days before the presentation of the dissertation, once the student's eligibility to take the Master's degree examination has been verified. With regard to the legal aspects related to the dissertation and its scientific outcomes (e.g. intellectual property of research outcomes), please refer to the relevant legislation and the University Regulations.
Evaluation of the dissertation
The Supervisor, the co-supervisor/s (if any) and the Examiner will evaluate the dissertation based on the following criteria:
- level of in-depth analysis carried out, in relation to the most recent developments in the areas related to information technology, with a focus on medical and biological applications;
- scientific and/or technological outcomes of the dissertation;
- student’s critical thinking;
- student’s experimental and/or formal development;
- student’s ability to carry out independent work (this point will not be assessed by the Examiner);
- value of the methodologies used;
- accuracy in planning and writing the dissertation.
Graduation mark
The graduation mark (based on a 110-point scale) is a whole value between 66/110 and 110/110 and is calculated by adding together the following elements (then rounding the result to the nearest whole number, e.g. 93.50 => 94; 86.49 => 86):
- 1) the average of the marks gained in the modules, weighted according to CFU, converted to a 110-point scale;
- 2) evaluation of the dissertation and the oral presentation during the final examination, based on the following methods:
- a) each of the points 1-7 listed above will be assigned a coefficient between 0 and 1 (fractional coefficient with one decimal place);
- b) the quality of the presentation will be assessed by awarding a coefficient between 0 and 1 (fractional coefficient with one decimal place);
- c) the sum of the points resulting from (a) and (b).
The Graduation Committee may award one extra point in the following cases: cum laude honours obtained in the exams taken during the degree programme; participation in internships officially recognised by the Computer Science Teaching Committee; taking extra modules; and the achievement of the degree in a time that is shorter than the normal duration of the degree programme. If the final score is 110/110, the Graduation Committee may award cum laude honours by unanimous decision.
External dissertations
An external dissertation is a work carried out in collaboration with an institution/body other than the University of Verona. In this case, the topic of the dissertation must be agreed in advance with a Supervisor from the University of Verona. In addition, the student must indicate at least one co- supervisor belonging to the external institution/body, who will support the student during the work on the dissertation. The Supervisor and the co- supervisors must be indicated in the online graduation application. The insurance aspects relating to the student's stay at the external institution are regulated by the regulations in force at the University of Verona. If the dissertation involves a period of training at the external institution/body, then it is necessary that the University of Verona enters into a specific agreement with such institution/body. The scientific outcomes of the dissertation will be available to all parties involved. In particular, the contents and results of the dissertation are to be considered public. For all matters not strictly scientific (e.g. agreements, insurance) the resolution of the Academic Senate of 12 January 1999 shall be taken as a reference.
Supervisor, co-supervisors, examiners
The dissertation presentation is introduced by the Supervisor. Professors belonging to the Master’s degree programme in Medical Bioinformatics, the Department of Computer Science, and any associated departments may be appointed as Supervisors, as well as any lecturers from the University of Verona whose area of interest is included in the Scientific-disciplinary Sectors (SSD) ING/INF/05 and INF/01. In addition to those who have the above requirements to be appointed as Supervisor, the following individuals may be appointed as co-supervisors: researchers working in external research institutes, research grant holders, post-doctoral fellowship holders, PhD students, technical staff of the Department, external experts appointed by an Italian University, corporate officers who have a remarkable experience in the field relevant to the topic of the dissertation. Examiners may be appointed among professors of the University of Verona, working in the Scientific- disciplinary Sectors (SSD) included in the educational offer of the Master’s degree programme in Medical Bioinformatics, and experts in the specific field of the dissertation topic.
Procedures and deadlines
The student who is about to complete their studies must identify a dissertation topic, proposed or approved by a Supervisor or co-supervisor/s (if any). When the work is nearing completion, the student must submit to the Teaching and Student Services Unit the graduation application, which must contain the title of the dissertation (even provisional), the name of the Supervisor, co-supervisor/s (only for external dissertations) and Examiner. Subsequently, on dates established by the Teaching and Student Services Unit, and in any case no later than 20 days before the graduation, the student must submit the graduation application form with the final title of the dissertation, which must be signed by the Supervisor. These documents must be delivered in accordance with the terms established by the Teaching and Student Services Unit.
The student will need to:
- i) upload a copy of their dissertation on ESSE3;
- ii) send a copy of their dissertation in PDF format to their Examiner.
In order to be admitted to the final examination, the student must have acquired the CFU in the SSD (Scientific-Disciplinary Sectors) set out in the Master’s degree regulations and teaching plan, and be up to date with the payment of their tuition fees. The Teaching and Student Services Unit of the Master's degree programme will invite all the Supervisors and co-supervisors involved, providing them with information about the date and time of the final examination.
Graduation Committee
The Graduation Committee shall include five members, of which at least four are professors in the Master's degree programme in Medical Bioinformatics. Based on the number of graduates, the Computer Science Teaching Committee will identify the most appropriate organisational methods for administering the examination, and it shall make available the calendar of tests at least one week before the examination itself. The procedures and deadlines for the submission of the graduation application are established by the Computer Science Teaching Committee and by the relevant offices.
Career management
Student login and resources
Erasmus+ and other experiences abroad
Tutoring faculty members
Attendance modes and venues
As stated in the Teaching Regulations, attendance at the course of study is not mandatory.
Part-time enrolment is permitted. Find out more on the Part-time enrolment possibilities page.
The course's teaching activities take place in the Science and Engineering area, which consists of the buildings of Ca‘ Vignal 1, Ca’ Vignal 2, Ca' Vignal 3 and Piramide, located in the Borgo Roma campus.
Lectures are held in the classrooms of Ca‘ Vignal 1, Ca’ Vignal 2 and Ca' Vignal 3, while practical exercises take place in the teaching laboratories dedicated to the various activities.