GMD@CSB.DB: the Golm Metabolome Database
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ID: 294893
2004
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Abstract
Summary: Metabolomics, in particular gas chromatography–mass spectrometry (GC–MS) based metabolite profiling of biological extracts, is rapidly becoming one of the cornerstones of functional genomics and systems biology. Metabolite profiling has profound applications in discovering the mode of action of drugs or herbicides, and in unravelling the effect of altered gene expression on metabolism and organism performance in biotechnological applications. As such the technology needs to be available to many laboratories. For this, an open exchange of information is required, like that already achieved for transcript and protein data. One of the key-steps in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations from biological samples. Collections of mass spectra, which comprise frequently observed metabolites of either known or unknown exact chemical structure, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here we present GMD, The Golm Metabolome Database, an open access metabolome database, which should enable these processes. GMD provides public access to custom mass spectral libraries, metabolite profiling experiments as well as additional information and tools, e.g. with regard to methods, spectral information or compounds. The main goal will be the representation of an exchange platform for experimental research activities and bioinformatics to develop and improve metabolomics by multidisciplinary cooperation. Availability: http://csbdb.mpimp-golm.mpg.de/gmd.html Contact: Steinhauser@mpimp-golm.mpg.de Supplementary information: http://csbdb.mpimp-golm.mpg.de/
| Reference Key |
openalex_W2151346683
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| Authors | Joachim Kopka, Nicolas Schauer, Stephan Krueger, Claudia Birkemeyer, Björn Usadel, E. Bergmuller, Peter Dörmann, Wolfram Weckwerth, Yves Gibon, Mark Stitt, Lothar Willmitzer, Alisdair R. Fernie, Dirk Steinhauser |
| Journal | BMC Bioinformatics |
| Year | 2004 |
| DOI |
10.1093/bioinformatics/bti236
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| URL | |
| Keywords | Keywords not found |
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