Translational Discovery Omics II - Proteomics
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, and functional protein interaction networks; and iii) introduction to clinical sample handling for proteome analysis and processing of proteomics data at different levels.
The main themes covered in the course include:
- Mass spectrometry technologies and principles for protein sequencing.
- Introduction to proteomics and applications in biology including examples with translational impact from industry and academia.
- Data analysis and visualization of proteomics data using StringApp and Cytoscape.
- Best practice for clinical sample handling, plasma proteomics hands-on workflow and data analysis.
BRIDGE - Translational Excellence Programme
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.
- Have a general understanding of the main statistical concepts required for proteomics data analysis.
- Understand the role of protein signalling pathways and functional protein interaction networks in health and disease.
Skills and Competences
- 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 signalling pathways and protein-protein interactions.
- Understand the important aspects of translational omics with a focus on clinical sample handling and be able to discuss and communicate these to other scientists, clinicians, and the public.
- Critically evaluate proteomic results and interpretation of downstream data analysis to answer biological questions and hypotheses.
The course is organized as a mix of lectures, practical
exercises, and laboratory work.
Lectures will introduce state-of the-art proteomics, applications and data analysis tools and include guest lecturers from academia/industry presenting proteomics work with translational impact. Practical exercises will allow course participants to learn-by-doing using concrete examples related to course content. Moreover, a significant part of the course will include a group-work-based lab exercise with hands-on training in clinical sample handling and proteomics analysis supervised by specialists in the field.
The course will end with an evaluation where participants must reflect on course learning outcomes and give feedback for course development.
Course literature will be published on Absalon.
Participants must meet the admission criteria in BRIDGE - Translational Excellence Programme.
The BRIDGE – Translational Excellence Programme offers a few selected 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 admission to the programme.
For further information about the programme, please go to the BRIDGE website: www.bridge.ku.dk
- 0 ECTS
- Type of assessment
Continuous assessmentCourse participation
- Type of assessment details
- Attendance and active participation. By active participation
the participant must demonstrate:
i) An overview of the major high-end quantitative proteomics technologies (label-free and tandem-mass-tag labelling) used for analysing 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 and functional protein interaction networks.
- All aids allowed
- Marking scale
- passed/not passed
- Censorship form
- No external censorship
Criteria for exam assessment
Active contribution and course participation according to the BRIDGE Guidelines and Practicalities.
Part time Master and Diploma courses
- Class Instruction
- Practical exercises
- Course number
- 0 ECTS
- Programme level
- Part Time Master
See course dates and course programme in Absalon
- 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 (12-706b79766b78347572796b744669767834717b346a71)
- Kristina Bennet Emdal (14-737a717b7c717669366d756c6974486b787a36737d366c73)
- Amelia Green (12-67736b726f67346d786b6b744669767834717b346a71)
- Moreno Papetti (14-75777a6d7677367869786d7c7c71486b787a36737d366c73)
Are you BA- or KA-student?
Courseinformation of students