Advanced bioinformatics for biotechnology

A.A. 2023/2024
6
Crediti massimi
48
Ore totali
SSD
BIO/11 INF/01
Lingua
Inglese
Obiettivi formativi
The course will discuss the practical and methodological aspects of some of the most widely used experimental techniques based on next-generation sequencing (NGS) from a bioinformatics point of view. First, transcriptome characterisation and quantification through RNA-Seq will be discussed in detail, also introducing the case of single-cell level (scRNA-Seq) approaches. The course will then introduce and discuss some of the most broadly used techniques for the characterisation of protein-DNA interactions at the genomic level (ChIP-Seq and other DNA-enrichment based techniques). Different state of the art approaches to the bioinformatic analysis of sequencing data will be outlined both methodologically and in practice. A focus on the proper handling of sequencing data will initiate the students to the importance of FAIR principles in modern bioinformatics.

Students will apply different bioinformatic tools and pipelines to selected case studies during classes. The course is ideally linked to those dealing with functional genomics and bioinformatics.
Risultati apprendimento attesi
At the end of this class, the students are expected to:
- be familiar with the most widely used protocols for sample preparation for RNA sequencing and be aware of the main principles underlying transcriptomes characterization and quantification;
- know the computational and methodological basics of standard bioinformatics protocols for RNA sequencing analysis, as well as being able to apply them to real case studies;
- know the computational and methodological basics of common bioinformatics protocols for single-cell RNA-Seq analysis and be able to apply them to real case studies;
- know the computational and methodological basics of standard bioinformatics protocols for characterising protein-DNA interactions at the genomic level and be able to apply them to real case studies.
- Be aware of the importance and role that FAIR principles have in bioinformatics data handling.
Corso singolo

Questo insegnamento può essere seguito come corso singolo.

Programma e organizzazione didattica

Edizione unica

Responsabile
Periodo
Secondo semestre

Programma
The course will present the computational and methodological basics of bioinformatics analysis of transcriptomic and protein-DNA interaction data. Theoretical explanations will be integrated by hands-on exercises in which students will apply the methods learnt to analyse real case studies.

In detail, the course will cover:

- General-purpose bioinformatics analysis tools for the Unix and R environments
- Experimental design of RNA sequencing assays
- RNA-seq data analysis for the characterisation and differential quantification of RNA molecules
- Basic principles of ChIP-sequencing and other DNA-enrichment-based techniques
- Analysis of Protein-DNA interactions (histone modifications, chromatin accessibility, transcription factors binding) data at the genomic level
- Introduction to FAIR principles for data handling in bioinformatics
Prerequisiti
Knowledge of the basics of genetics and molecular biology with particular reference to transcription, gene expression regulation, and nucleic acids sequencing. Familiarity with the R programming language. Understanding of the basics of probability and statistical testing. Students who passed the "Functional Genomics and Bioinformatics" and "Methods in Bioinformatics" exams with good marks should have acquired all or most of the recommended knowledge and competencies.
Metodi didattici
Lectures supported by projected material will be alternated with practical sessions in which students will apply bioinformatic tools and pipelines to the analysis of real case studies. Attendance is highly recommended.
Materiale di riferimento
Copies of the slides projected in the classroom and materials used in hands-on exercises will be made available through the course Ariel page. This material is intended to support lectures, and its study cannot be considered a full alternative to the constant attendance of classes. The material is made available only to registered students of the Degree Course in Molecular Biotechnology and Bioinformatics and should not be distributed to others without the express consent of the teacher. Selected articles describing the bioinformatics tools employed and the respective user manuals will also be provided.
Modalità di verifica dell’apprendimento e criteri di valutazione
Students will be assigned projects to analyse different data sets to be developed individually or in small groups of two people. At the exam, they will orally discuss the employed bioinformatics workflows, interpret the results obtained, and answer questions on the topics covered by the course. The evaluation will consider the knowledge of the analytical approaches employed, the ability to frame the biological meaning of the results obtained, and, more broadly, the general understanding of the topics covered by the course.
BIO/11 - BIOLOGIA MOLECOLARE
INF/01 - INFORMATICA
Lectures: 48 ore
Docente/i
Ricevimento:
Venerdì 15.00-16.00 previo appuntamento
Beacon Lab, Piano 2, Torre B, Dip. Bioscienze o su MS Teams