The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.
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The authors gratefully acknowledge the United Kingdom Food Standards Agency (under the G02006 project), the United Kingdom Biotechnology and Biological Sciences Research Council (particularly under the HiMet project) and the United Kingdom Engineering and Physical Sciences Research Council for support of their work in metabolomics. We would also like to thank personnel at the United Kingdom Institute of Grassland and Environmental Research and delegates at the 1st, 2nd and 3rd International Plant Metabolomics Conferences for many useful discussions.
The authors declare no competing financial interests.
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