Summer School on Non-Targeted Metabolomics Data Mining for Biomedical Research
In collaboration with Aarhus University and the University of Tübingen, Statens Serum Institut is hosting the 3rd International Summer School on Non-Targeted Metabolomics Data Mining for Biomedical Research.
Date
21st-25th of August 2023
Location
Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
Program
3rd International Summer School on NON-TARGETED METABOLOMICS DATA MINING FOR BIOMEDICAL RESEARCH (pdf)
Course credits
5 ECTS credits
Costs
Academic 400 €, Industry 700 €, waivers for low-income participants. The costs include lunch for all five course days.
Overview
The summer school will introduce non-targeted mass spectrometry-based metabolomics with a strong focus on biomedical research and hands-on training in metabolomics data mining tools. The summer school is offered through a collaboration between Aarhus University, the University of Tübingen, and Statens Serum Institut.
Goals
We will briefly introduce analytical hardware, acquisition strategies, study design, sample preparation, and quality control. The main focus will be on working with state-of-the-art metabolomics data mining tools for preprocessing, compound annotation, and statistical analysis.
Instructors
- Madeleine Ernst (Statens Serum Institut, Denmark)
- Markus Fleischauer (Friedrich-Schiller University Jena, Germany)
- Martin Hansen (Aarhus University, Denmark)
- Steffen Heuckeroth (University of Münster, Germany)
- Florian Huber (Düsseldorf University of Applied Sciences, Germany)
- Alan Jarmusch (National Institute of Environmental Health Sciences, United States)
- Scott Jarmusch (Technical University of Denmark)
- Efi Kontou (Technical University of Denmark)
- Fleming Kretschmer (Friedrich-Schiller University Jena, Germany)
- Filip Ljung (Statens Serum Institut, Denmark)
- Filip Ottosson (Statens Serum Institut, Denmark)
- Daniel Petras (University of Tübingen, Germany)
- Robin Schmid (Institute of Organic Chemistry and Biochemistry Prague, Czech Republic)
- Abzer K. Pakkir Shah (University of Tübingen, Germany)
- Justin J.J. van der Hooft (Wageningen University & Research, the Netherlands)
- Ming Wang (online) (University of California - Riverside, United States)
- and more…
Form
- 5-day hands-on intensive course
- Assigned reading package
- Active participation in class discussions and working groups
- Course assignment in working groups
Course requirements
The summer school takes place as a five days intensive course. Prior to the course, the participants are expected to have familiarized themselves with the listed literature. It is expected that all participants are highly active in the workshops. On the final day, the participants will present their (workshop) results to have their performance assessed.
Learning outcomes and competencies
At the end of the course, the student should be able to:
- Understand basic principles of high-resolution tandem mass spectrometry
- Understand typical mass spectrometry data formats
- Carry out data pre-processing using MZmine
- Understand and apply metabolite identification confidence levels
- Use and understand tools for advanced metabolite identification (e.g. GNPS, MS2LDA, Matchms and Sirius+CSI:FingerID)
- Understand and use basic multi- and univariate statistical methods, e.g. PCA, and differential analysis
- Perform a full workflow for basic analysis of a non-targeted metabolomics experiment, including data preprocessing, metabolite annotation, statistical analysis, and biological interpretation
Prerequisites
- MSc in natural sciences or related field
- Experience in R, Python, or any metabolomics preprocessing software (e.g. MZmine, XCMS, OpenMS) or compound annotation tool (e.g. GNPS, MS2LDA, Sirius+CSI:FingerID, Matchms) is of advantage