Bioinformatics (2019/2020)

Course code
Name of lecturer
Nicola Vitulo
Nicola Vitulo
Number of ECTS credits allocated
Other available courses
Academic sector
Language of instruction
I semestre dal Oct 1, 2019 al Jan 31, 2020.

Lesson timetable

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Learning outcomes

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.


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

Assessment methods and criteria

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.