ID:
510329
Duration (hours):
60
CFU:
6
SSD:
BIOLOGIA MOLECOLARE
Year:
2025
Overview
Date/time interval
Primo Semestre (29/09/2025 - 16/01/2026)
Syllabus
Course Objectives
At the end of this class, the students are expected to:
-Understand the nature and differences in the biological information delivered by different sequencing technologies (i.e. whole genome, whole exome, transcriptome sequencing)
-Identify the key factors in designing genomics and transcriptomics experiments ( number of replicates, library construction, run type, coverage, and depth)
-Understand the computational and statistical requirements of the main bioinformatics applications (computing infrastructures, memory, cores, storage)
-Apply infrastructure knowledge and integrate it with a biological understanding of the experiments to design and execute variant calling and RNA sequencing analysis workflows
-Solve a given biological problem by choosing the appropriate tools and workflows, develop and report a hypothesis from the biological interpretations of the results
-Understand the nature and differences in the biological information delivered by different sequencing technologies (i.e. whole genome, whole exome, transcriptome sequencing)
-Identify the key factors in designing genomics and transcriptomics experiments ( number of replicates, library construction, run type, coverage, and depth)
-Understand the computational and statistical requirements of the main bioinformatics applications (computing infrastructures, memory, cores, storage)
-Apply infrastructure knowledge and integrate it with a biological understanding of the experiments to design and execute variant calling and RNA sequencing analysis workflows
-Solve a given biological problem by choosing the appropriate tools and workflows, develop and report a hypothesis from the biological interpretations of the results
Course Prerequisites
Knowledge of basic concepts in molecular biology and genetics (including the structure and function of DNA, RNA, and proteins; processes such as replication, transcription, translation, splicing, sequencing; variants, allele fraction, haplotype and genotype, and the PCR method); basic descriptive statistics (including mean and variance); working knowledge of Linux-based environments and cloud computing infrastructures.
Teaching Methods
Class activities will emphasize demonstrations, classroom discussions, and interactive problem-solving sessions. Students will participate in demos, engage in group work, and take quizzes to reinforce their learning. Real-time feedback will be provided to support their progress. The Kiro platform will be utilized for readings and self-evaluation activities, enhancing the overall learning experience. The most appropriate inclusive educational methods will be implemented, to meet the needs of specific categories of students defined by the University.
Assessment Methods
As part of a project assignment, students will receive simplified datasets to analyse using the tools and methods taught during the course. During the oral examination, students will be evaluated based on their ability to effectively interpret and explain the results of their analysis, demonstrate a critical approach in addressing the given biological question, and showcase their proficiency in utilising the appropriate tools and methods.
Texts
The course will mostly use freely available material, tutorials and slides. Some reference textbooks are indicated below:
Geraldine A. Van der Auwera, Brian D. O'Connor, Genomics in the Cloud, 2020, O'Reilly Media, Inc., ISBN: 9781491975190
Geraldine A. Van der Auwera, Brian D. O'Connor, Genomics in the Cloud, 2020, O'Reilly Media, Inc., ISBN: 9781491975190
Contents
The course will deal the following topics:
- Use of Nextflow in cloud environments
- RNA-seq data analysis: experimental design and differential gene expression analysis, biological interpretation and execution of standard workflows in a cloud environment
- Resequencing data analysis: experimental design and variant calling best practices, annotation, and execution of standard workflows in a cloud environment
- Databases for the interpretation of variant calling and transcriptomics results
- Proteomics data analysis: Macromolecular Structure Prediction and Analysis, Molecular docking, MD simulation and modeling
- Use of Nextflow in cloud environments
- RNA-seq data analysis: experimental design and differential gene expression analysis, biological interpretation and execution of standard workflows in a cloud environment
- Resequencing data analysis: experimental design and variant calling best practices, annotation, and execution of standard workflows in a cloud environment
- Databases for the interpretation of variant calling and transcriptomics results
- Proteomics data analysis: Macromolecular Structure Prediction and Analysis, Molecular docking, MD simulation and modeling
Course Language
English
More information
The teachers will be available via email and Slack, and for meetings to be agreed on.
Degrees
Degrees
MOLECULAR BIOLOGY AND GENETICS
Master’s Degree
2 years
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People
People (2)
Teaching staff
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