https://www.dagstuhl.de/15492
November 29 – December 4 , 2015, Dagstuhl Seminar 15492
Computational Metabolomics
Organizers
Sebastian Böcker (Universität Jena, DE)
Oliver Fiehn (University of California – Davis, US)
Juho Rousu (Aalto University, FI)
Emma Schymanski (Eawag – Dübendorf, CH)
For support, please contact
Documents
Dagstuhl Report, Volume 5, Issue 11
Aims & Scope
List of Participants
Shared Documents
Dagstuhl Seminar Wiki
(Use seminar number and access code to log in)
Summary
Metabolomics has been referred to as the apogee of the omics-sciences, as it is closest to the biological phenotype. Mass spectrometry is the predominant analytical technique for detecting and identifying metabolites and other small molecules in high-throughput experiments. Huge technological advances in mass spectrometers and experimental workflows during the last decades enable novel investigations of biological systems on the metabolite level. But these advances also resulted in a tremendous increase of both amount and complexity of the experimental data, such that the data processing and identification of the detected metabolites form the largest bottlenecks in high throughput analysis. Unlike proteomics, where close co-operations between experimental and computational scientists have been established over the last decade, such cooperation is still in its infancy for metabolomics.
The Dagstuhl Seminar on Computational Metabolomics brought together leading experimental and computational side experts in a dynamically-organized seminar designed to foster the exchange of expertise. Overview talks were followed by breakout sessions on topics covering the whole experimental-computational continuum in mass spectrometry.


Dagstuhl Seminar Series
- 22181: "Computational Metabolomics: From Spectra to Knowledge" (2022)
- 20051: "Computational Metabolomics: From Cheminformatics to Machine Learning" (2020)
- 17491: "Computational Metabolomics: Identification, Interpretation, Imaging" (2017)
Classification
- Bioinformatics
Keywords
- Bioinformatics
- Cheminformatics
- Computational metabolomics
- Computational mass spectrometry
- Algorithms
- Databases