Teaching Academic Courses

Academic Courses

Members of the COMBINE Lab are deeply committed to training and mentoring the next generation of bioengineers and biotechnologists. At the University of Florence, we offer specialized courses designed to bridge the gap between computational data science and life sciences. Full details on schedules, programs, and enrollment can be explored directly through the official UniFi course registry.

Computational genomics (Genomica Computazionale)

• Instructor: Prof. Alberto Magi
• Degree Program: Master's Degree in Biomedical Engineering (Laurea Magistrale in Ingegneria Biomedica)
• Credits: 6 CFU
• Course Description: This course provides a comprehensive introduction to genomics and the primary sources of genetic variation, including SNVs, small indels, and structural variants. Students will explore microarray and Next-Generation Sequencing (NGS) technologies, focusing on experimental design, read alignment, coverage analysis, and statistical methods for variant calling. The curriculum also covers essential software tools for genomic variant analysis and functional annotation, with a specific emphasis on assessing impacts on proteins and regulatory regions. Finally, the course delves into third-generation sequencing approaches, including cutting-edge methods for long-read variant discovery and haplotype reconstruction.

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System Biology

• Instructor: Prof. Alberto Magi
• Degree Program: Master's Degree in Biomedical Engineering (Laurea Magistrale in Ingegneria Biomedica)
• Credits: 6 CFU
• Course Description: This course bridges experimental and computational biology, starting with a foundation in molecular biology (DNA, RNA, proteins, and the Central Dogma) and key experimental techniques such as PCR, microarrays, NGS, and third-generation sequencing. Moving from the bench to data analysis (Dry Biology), students will explore genomics, transcriptomics, and epigenomics, focusing on variant calling, gene expression, and methylome analysis. Finally, the course introduces Network Biology, covering protein-protein interactions and the foundational principles of network medicine.

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Single Cell Omics

• Instructor: Dr. Roberto Semeraro
• Degree Program: Master's Degree in Biomedical Engineering (Laurea Magistrale in Ingegneria Biomedica)
• Credits: 6 CFU
• Course Description: This course introduces students to the foundations of Systems Biology and biological networks, exploring the major multi-omics layers including genomics, transcriptomics, proteomics, metabolomics, and epigenomics. It examines pre-single-cell integromics through real-world case studies, such as the LOAD study, before diving into the history, applications, and experimental design of single-cell technologies. Students will gain a comprehensive overview of single-cell data processing, with hands-on experience in data analysis using Python. Finally, the curriculum covers advanced topics in single-cell data integration and its applications within interactomics.