MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics |
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| Authors: | Irena Spasić Warwick B Dunn Giles Velarde Andy Tseng Helen Jenkins Nigel Hardy Stephen G Oliver Douglas B Kell |
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| Affiliation: | (1) School of Chemistry, Faraday Building, The University of Manchester, Manchester, M60 1QD, UK;(2) Department of Computer Science, The University of Wales, Aberystwyth, SY23 3DB, UK;(3) Faculty of Life Sciences, Michael Smith Building, The University of Manchester, Manchester, M13 9PT, UK |
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| Abstract: | Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. |
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