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Nucleic Acids Research Advance Access originally published online on April 28, 2008
Nucleic Acids Research 2008 36(Web Server issue):W481-W484; doi:10.1093/nar/gkn194
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Nucleic Acids Research, 2008, Vol. 36, No. suppl_2 W481-W484
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles

MassTRIX: mass translator into pathways

Karsten Suhre1,2,* and Philippe Schmitt-Kopplin3

1Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, 2Department of Biology, University of Munich (LMU), Großhaderner Straße 2, 82152 Planegg-Martinsried and 3Institute of Ecological Chemistry, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany

*To whom correspondence should be addressed. Tel: +49 89 3187 2627; Fax: +49 89 3187 3585; Email: karsten.suhre{at}helmholtz-muenchen.de

Received January 30, 2008. Revised March 26, 2008. Accepted April 2, 2008.

Recent technical advances in mass spectrometry (MS) have brought the field of metabolomics to a point where large numbers of metabolites from numerous prokaryotic and eukaryotic organisms can now be easily and precisely detected. The challenge today lies in the correct annotation of these metabolites on the basis of their accurate measured masses. Assignment of bulk chemical formula is generally possible, but without consideration of the biological and genomic context, concrete metabolite annotations remain difficult and uncertain. MassTRIX responds to this challenge by providing a hypothesis-driven approach to high precision MS data annotation. It presents the identified chemical compounds in their genomic context as differentially colored objects on KEGG pathway maps. Information on gene transcription or differences in the gene complement (e.g. samples from different bacterial strains) can be easily added. The user can thus interpret the metabolic state of the organism in the context of its potential and, in the case of submitted transcriptomics data, real enzymatic capacities. The MassTRIX web server is freely accessible at http://masstrix.org


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