Advanced Bioinformatics for Biotechnology
A.Y. 2020/2021
Learning objectives
The course will present some of the most widely used experimental techniques based on next-generation sequencing (NGS) for transcriptome characterization and quantification (RNA-Seq). Different state of the art approaches to the bioinformatic analysis of RNA-Seq data will be outlined both in theory and in practice. During lab classes, students will apply different bioinformatic tools and pipelines to selected case studies. The course is ideally linked to those dealing with functional genomics and bioinformatics.
Expected learning outcomes
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;
- know the computational and statistical basics of the main bioinformatic protocols for RNA sequencing (transcript assembly and gene annotation), as well as being able to apply them to real case studies;
- know the computational and statistical basics of the main bioinformatic protocols for transcript quantification from RNA sequencing and for subsequent analyses (clustering, identification of differentially expressed genes, etc.), as well as being able to apply them to real case studies;
- know the computational and statistical basics of the main bioinformatic protocols for single cell RNA-Seq analysis, as well as being able to apply them to real case studies.
- be familiar with the most widely used protocols for sample preparation for RNA sequencing;
- know the computational and statistical basics of the main bioinformatic protocols for RNA sequencing (transcript assembly and gene annotation), as well as being able to apply them to real case studies;
- know the computational and statistical basics of the main bioinformatic protocols for transcript quantification from RNA sequencing and for subsequent analyses (clustering, identification of differentially expressed genes, etc.), as well as being able to apply them to real case studies;
- know the computational and statistical basics of the main bioinformatic protocols for single cell RNA-Seq analysis, as well as being able to apply them to real case studies.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
BIO/11 - MOLECULAR BIOLOGY
INF/01 - INFORMATICS
INF/01 - INFORMATICS
Lectures: 48 hours
Professors:
Bombarely Gomez Aureliano, Pavesi Giulio, Zambelli Federico
Professor(s)
Reception:
Tuesday or Friday, h. 15.00- 17.00
Via Celoria 26 (Department of Biosciences)/Online
Reception:
Friday 15.00-16.00 by appointment
Beacon Lab, 2nd floor, B Tower, Dept. of Biosciences / MS Teams