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 magistrale in Molecular and Medical Biotechnology - Enrollment from 2025/2026

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.

activated in the A.Y. 2023/2024
ModulesCreditsTAFSSD
Modules Credits TAF SSD
Between the years: 1°- 2°
2 courses among the following ("BIOTECHNOLOGY IN NEUROSCIENCE" 1ST YEAR; "CLINICAL PROTEOMICS" 1ST and2ND YEAR; the other courses 2nd year only)

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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S003667

Coordinator

Nicola Vitulo

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

BIO/18 - GENETICS

Period

Semester 2 dal Mar 6, 2023 al Jun 16, 2023.

Learning objectives

The advent of the new sequencing technology (Next Generation Sequencing, NGS) had a great impact on the ability to study genome complexity at genomic, transcriptomic and epigenetic level and provided interesting opportunities for the development of bioinfomatic resources for data analyses and management. The course will provide a general overview of the main computational methods based in NGS data that can be applied in genomic studies (mainly focused on the human genome) as for example , sequence alignment, genome sequencing, genome resequencing for the identification of variants, transcriptomic analysis for the identification of differentially expressed genes. At the end of the course the student should be able to: Know the main data file formats Know the different algorithm used in genomic studies and their applications Setting up a pipeline for data managing and analysis

Prerequisites and basic notions

No specific prerequisites are required. Basic knowledge of bioinformatics (eg sequence alignment) may be useful but not essential to better understand the program.

Program

1. Introduction to Next Generation Sequencing (NGS) data
a. Illumination bias and sequencing errors
b. FastQ format
c. Checking the quality of the sequences d. Sequence preprocessing
2. Overview of genome assembly methods
a. Overlap-layout-consensus
b. Debrujin graph
c. Assembly quality verification
3. Alignment of NGS data on a reference genome
a. Dynamic programming
b. Heuristic methods
c. SAM / BAM format
4. Re-sequencing and calling variants
a. Identification of germline variants
b. Identification of somatic variants
c. Bioinformatics methods for the identification of structural variants d. VCF and gVCF file format
5. Computational methods for the prioritization of candidate genes
6. Analysis of transcriptomics and RNA-seq data
a. Alignment of RNA-seq sequences
b. Reconstruction of transcripts (genome-guided / denovo)
c. Gene quantification
d. Data normalization
e. Identification of differentially expressed genes
f. Enrichment analysis

Laboratory

Some lessons will be devoted to exercises carried out with the computer. In particular, the following topics will be addressed:
- Use of the main bash commands
- Execution of some programs studied in class
- Development of simple pipelines for data analysis

Didactic methods

The teaching methods adopted in the course are:
- Frontal lessons
- Computer laboratory exercises
- Reading and presentation of scientific articles

Learning assessment procedures

The exam consists of a written verification of the level of knowledge regarding the argument of the course. The exam consist of six open questions. The student need to demonstrate the understanding of the method and application of the major bioinformatic programs and approaches learned during 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

Evaluation criteria

The level of understanding of the topics and the language properties will be evaluated

Criteria for the composition of the final grade

Each question will be assigned a score of 10, the final grade will be scaled to 30.
The presentation of scientific articles is not compulsory, students who intend to submit a scientific article can have a bonus of up to two points to be added to the grade of the exam

Exam language

Italiano/Inglese