The eMetabolomics research project

The eMetabolomics project is funded by the Netherlands eScience Center and is carried out at Wageningen University and the Netherlands eScience Center in collaboration with the Netherlands Metabolomics Centre. The project develops chemo-informatics based methods for metabolite identification and biochemical network reconstruction in an integrative metabolomics data analysis workflow.

MAGMa Online

MAGMa is an online application for the automatic chemical annotation of accurate multistage MSn spectral data.

  • MSn data can be uploaded as a hierarchical tree of fragment peaks, either based on m/z values or elemental formulas, or as an mzXML file of the raw data.
  • Candidate molecules are automatically retrieved from PubChem, from a subset of PubChem compounds present in Kegg, or from the Human Metabolome Database.
  • Candidate molecules can be predicted based on in silico reaction rules describing microbiotic and human biotransformations
  • For each candidate molecule, substructures are generated and matched with the observed fragment peaks.
  • The web browser enables efficient mining of the automatically annotated data.
  • Open Source, source code available at

The online webservice is currently not available


  1. The MAGMa algorithm for substructure based annotation of multistage MSn spectra is described in Ridder et al. 2012.
  2. Ridder et al. 2013: MAGMa is used for the automatic annotation of a complete metabolite profile of green tea.
  3. Ridder et al. 2014a: The new metabolite prediction module in MAGMa is used to annotate urinary metabolites of the compounds in green tea. The generated library of 27245 potential green tea derived metabolite structures can be downloaded for reuse in other studies: please refer to the Ridder 2014 paper.
  4. Prize-winning poster presented at the Analytical Tools for Cutting-edge Metabolomics meeting in London, 30 April 2014
  5. MAGMa was selected as "best automated method" in the international CASMI contest 2013. The MAGMa entry is described by Ridder et al. (2014b).
  6. The MAGMa solutions were also submitted to the international CASMI contest 2014.

For more information or feedback, contact: Lars Ridder