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
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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One course among the followingOne course among the followingTwo courses among the followingThree courses among the following2° Year It will be activated in the A.Y. 2026/2027
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| Modules | Credits | TAF | SSD |
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One course among the followingOne course among the followingTwo courses among the followingThree courses among the following| Modules | Credits | TAF | SSD |
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| Modules | Credits | TAF | SSD |
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Two courses among:
- 2nd year - Molecular farming, Toxicology and applied pharmacology, Systems biology, Radioactivity and radiation protection - delivered in 2026/2027
- 1st and 2nd year - Biotechnology in neuroscience, Clinical proteomics - delivered in 2025/2026 and 2026/2027
A.A. 2025/2026: BIOTECHNOLOGY IN NEUROSCIENCE not available 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.
Computational genomics (2025/2026)
Teaching code
4S003667
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
BIO/18 - GENETICS
Period
2nd semester dal Mar 2, 2026 al Jun 12, 2026.
Courses Single
Authorized
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 (e.g., sequence alignment) may be helpful but is not essential to better understand the program.
Program
1. Introduction to Next-Generation Sequencing (NGS) Data a. Illumina Sequencing Bias and Errors b. FastQ Format c. Sequence Quality Verification 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 to a Reference Genome a. Dynamic Programming b. Heuristic Methods c. SAM/BAM Format 4. Resequencing and Variant Calling a. Germline Variant Calling b. Somatic Variant Calling c. Bioinformatics Methods for Structural Variant Calling d. VCF and gVCF File Format 5. Computational Methods for Candidate Gene Prioritization 6. Analysis of Transcriptomics and RNA-Seq Data a. RNA-Seq Sequence Alignment b. Transcript Reconstruction (Genome-Guided / Denovo) c. Gene quantification d. Data normalization e. Identification of differentially expressed genes f. Enrichment analysis
Bibliography
Didactic methods
The teaching methods adopted in the course are: - Frontal lectures - Computer laboratory exercises - Reading and presentation of scientific articles
Learning assessment procedures
The exam consists of a written test of the student's knowledge of the topics covered in the course. The exam consists of six open-ended questions. Students must demonstrate their understanding of the operation and application of the main bioinformatics programs and approaches explained in class.
Evaluation criteria
The level of understanding of the topics and the command of language will be assessed.
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 mandatory, students who intend to present a scientific article will have a bonus of up to two points to be added to the exam grade.
Exam language
Preferenzialmente inglese
