SBRI19002U Translational Discovery Omics II - Proteomics
BRIDGE - Translational Excellence Programme
The main themes covered in the course include:
- Mass spectrometry technologies and principles for protein sequencing.
- Introduction to proteomics and applications in biology with examples from industry and academia
- Best practice for clinical sample handling, plasma proteomics hands-on workflow and data analysis
The aim of the course is to provide the participants with: i) an
overview of the major high-end quantitative proteomics technologies
with focus on mass spectrometry; ii) an overview of key biological
applications that quantitative proteomics screens can be applied
in, including proteome quantitation, post-translational
modification (PTM) analysis and functional protein interaction
networks iii) introduction to clinical sample handling for proteome
analysis and processing of proteomics data at different levels.
Upon completing the course, participants should be able to:
- Demonstrate a basic understanding of different mass spectrometry-based proteomics workflows, experimental design and methods including hands-on experience with plasma proteomics.
- Gain a general understanding of the main statistical concepts required for proteomics.
- Understand the role of protein signaling pathways and functional protein interaction networks in health and disease.
Skills and Competences
- Ablility to perform mass spectrometry-based proteome analysis of biological and clinical samples.
- Process raw mass spectrometry data and obtain peptide and protein identification from proteome analysis using different software tools (MaxQuant, Spectronaut).
- Use data analysis and visualization programs such as Perseus, StringApp, and Cytoscape including ability to integrate proteomics data with curated datasets such as signaling pathways and protein-protein interactions.
- Understand the important aspects of translational omics and be able to discuss and communicate these to other scientists, clinicians, and the public.
- Critically evaluate the results and interpretation of downstream data analysis to answer biological questions and hypotheses.
Course literature is published on Absalon.
- Class Instruction
- Practical exercises
The BRIDGE – Translational Excellence Programme offers a few
select graduated PhDs a two-year postdoctoral fellowship in
translational medicine. The courses are only available to the
fellows enrolled in the programme. Fellows are automatically
enrolled in the courses upon appointment in the programme.
For further information: https://bridge.ku.dk/about/
- 0 ECTS
- Type of assessment
- Continuous assessmentCourse participation
- Type of assessment details
- Attendance and active participation
- Exam registration requirements
Participants are automatically registered for the Examination upon course registration.
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Criteria for exam assesment
Active contribution and course participation according to the BRIDGE Guidelines.
By active participation the student must demonstrate:
i) An overview of the major high-end quantitative proteomics technologies (label-free and tandem-mass-tag labeling) used for analyzing patient and biological samples using high-resolution mass spectrometry,
ii) Knowledge on standard go-to software solutions for raw mass spectrometry data analysis including downstream software packages for data interpretation and basic visualization
iii) Knowledge of important factors influencing pre-analytical sample variability and optimal experimental design for analysis of clinical samples.
iv) Knowledge of biological applications using quantitative proteomics including proteome quantitation, analysis of post-translational modifications, and functional protein interaction networks.
- Course code
- 0 ECTS
- Part Time MasterPh.D.
- See course dates and course programme in Absalon
- Course capacity
- 15 participants
- Study Board for the Professionel Master´s Degree Programmes at The Faculty og Health and Medical Science
- Center for Protein Research
- Faculty of Health and Medical Sciences
- Jesper Velgaard Olsen (12-6e697774697632737077697244677476326f7932686f)
- Moreno Papetti (14-7375786b7475347667766b7a7a6f4669767834717b346a71)
- Kristina Bennet Emdal (14-71786f797a6f7467346b736a67724669767834717b346a71)