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A systematic approach to modeling, capturing, and disseminating proteomics experimental data.

Chris F Taylor·Norman W Paton·Kevin L Garwood·Paul D Kirby·David A Stead·Zhikang Yin·Eric W Deutsch·Laura Selway·Janet Walker·Isabel Riba-Garcia·Shabaz Mohammed·Michael J Deery·Julie A Howard·Tom Dunkley·Ruedi Aebersold·Douglas B Kell·Kathryn S Lilley·Peter Roepstorff·John R Yates·Andy Brass·Alistair J P Brown·Phil Cash·Simon J Gaskell·Simon J Hubbard·Stephen G Oliver
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Abstract

Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.

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Database Management SystemsDatabases, ProteinDocumentationHypermediaInformation DisseminationInformation Storage and RetrievalModels, MolecularProtein ConformationProteinsProteomicsSequence Analysis, ProteinSoftwareSoftware DesignUser-Computer InterfaceJournal ArticleResearch Support, Non-U.S. Gov't

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Chris F Taylor, Norman W Paton, Kevin L Garwood, Paul D Kirby, David A Stead, Zhikang Yin, Eric W Deutsch, Laura Selway, Janet Walker, Isabel Riba-Garcia, Shabaz Mohammed, Michael J Deery, Julie A Howard, Tom Dunkley, Ruedi Aebersold, Douglas B Kell, Kathryn S Lilley, Peter Roepstorff, John R Yates, Andy Brass, Alistair J P Brown, Phil Cash, Simon J Gaskell, Simon J Hubbard, Stephen G Oliver. 2003. A systematic approach to modeling, capturing, and disseminating proteomics experimental data.. https://doi.org/10.1038/nbt0303-247

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