Teaching code

4S00183

Teacher

Nicola Vitulo

Coordinator

Nicola Vitulo

Credits

6

Also offered in courses:

• Bioinformatics of the course Master's degree in Agri-Food Biotechnology

Language

Italian

Scientific Disciplinary Sector (SSD)

BIO/11 - MOLECULAR BIOLOGY

Period

Semester 1 dal Oct 3, 2022 al Jan 27, 2023.

Lessons timetable Moodle Seminars 0

Learning objectives

Over the last decade the technological improvements of sequencing technologies (Next Generation Sequencing, NGS) had an enormous impact on the understanding of the genomes complexity and had provided interesting opportunities for the development of bioinformatics tools and programs for data analysis and management. The course aims to provide a general overview of the different computational methods applied in the field of NGS and omics science. These new technologies, which made possible to move from a reductionist to a holistic approach, have made it necessary to develop new strong interdisciplinary methods for data interpretation and integration. The course will provide students with basic knowledge on bioinformatics tools for the interpretation and integration of different omics data applied to the study of genomes, of gene expression and of metagenomic data for community analysis and microbial characterization. The course will also include a part performed in a computer lab where the computational programs necessary for the manipulation and interpretation of biological data will be illustrated.

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

Introduction to next-generation sequencing data (NGS)
a. Bias and technology sequencing errors illuminate
b. FastQ format
c. Sequences quality check
d. Sequences pre-processing
2. NGS data alignment on a reference genome
a. Alignment of genomic and rna-seq sequences
b. SAM / BAM format
3. Analysis of transcriptomic data and RNA-seq
a. Transcripts reconstruction (genome-guided / denovo)
b. Gene quantification
c. Data normalization
d. Identification of differentially expressed genes
4. Genomes analysis
a. Genome assembly
b. Resequencing and identification of variants
c. Structural variants
d. VCF and gVCF file format
5. Computational methods for the analysis of metagenomic data
a. Metabarcoding
b. Whole Metagenome Sequencing
c. Taxonomic assignment
d. Metrics for the analysis of microbial complexity (alpha and beta diversity)
6. Introduction to system biology and omics data integration

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.

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