Module Details

Cytomics

MS2134

Course
Cytomics
Code
MS2134
Academic Year
2026/2027
Curriculum Year
2025/2026
Degree Programme
MEDICAL BIOTECHNOLOGY
Curriculum
A006 - SYSTEM BIOMEDICINE
Course coordinator
Lecturers
Credits
1
Lecture Hours
10
Scientific Disciplinary Sector (SSD)
MED/04 - General Pathology
Course Type
Single-subject learning activity
Course Delivery
OBB - Obbligatoria
Year
2
Teaching period
Secondo Semestre
Campus
NOVARA
Teaching language
English
Course Contents

The course, after a review of basic immunology and the explanation of the basic concepts of flow cytometry, addresses the topics of multiparametric cytometry, scRNA-seq and mass image analysis. Focusing the attention of the course on single cell analysis techniques through the use of different algorithms.

Reference Texts

none

Learning Outcomes

The course aims to apply single cell analysis techniques using different algorithms. Applying these techniques to multiparametric cytometry, image mass cytometry and scRNA-seq.

Prerequisites

Knowledge on basic Immunological processes

Teaching Methods

Frontal lessons

Additional Information

Students with physical disabilities, Learning Disabilities or Special Education Needs can request

specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse

e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-

students-physical-or-learning-disabilities

Students with disabilities, learning disabilities or special education needs, once they have contacted

the University Staff, can refer to the tutor in charge of the course to define the examination

modalities, concerning academic aspects.

Assessment Methods

Written exam with questions with true/false answers and subsequent explanation

Detailed Syllabus

Flow cytometry: basic concepts and its applications. scRNA-seq: basic concepts and applications. Image mass cytometry: basic concepts and its applications. Single cell analysis techniques using different algorithms (dimensionality reduction, clustering algorithm, classification algorithm). SEURAT pipeline

Expected Learning Outcomes

Students will have to demonstrate knowledge of the main single cell techniques and complex data analysis techniques (multiparametric cytometry, scRNA-seq and image mass cytometry)

Last update:04-10-2026 00:15:57