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

C. F. Taylor, N. W. Paton, K. L. Garwood, P. D. Kirby, David Andrew Stead, Zhikang Yin, E. Deutsch, Laura Selway, Janet Walker, I. Riba-Garcia, S. Mohammed, M. Deery, J. Howard, T. Dunkley, R. Aebersold, D. Kell, A. Lilley, P. Roepstorff, J. R. Yates, A. Brass & 5 others Alistair James Petersen Brown, Phillip Cash, S. Gaskell, S. Hubbard, S. G. Oliver

Research output: Contribution to journalArticle

218 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)247-254
Number of pages8
JournalNature Biotechnology
Volume21
Issue number3
DOIs
Publication statusPublished - Mar 2003

Fingerprint

Proteomics
XML
Language
Proteome
Microarrays
Proteins
Unified Modeling Language
Query languages
Experiments
Gene expression
Throughput
Guidelines
Technology
Gene Expression

Keywords

  • protein

Cite this

Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D., Stead, D. A., Yin, Z., ... Oliver, S. G. (2003). A systematic approach to modeling, capturing, and disseminating proteomics experimental data. Nature Biotechnology, 21(3), 247-254. https://doi.org/10.1038/nbt0303-247

A systematic approach to modeling, capturing, and disseminating proteomics experimental data. / Taylor, C. F.; Paton, N. W.; Garwood, K. L.; Kirby, P. D.; Stead, David Andrew; Yin, Zhikang; Deutsch, E.; Selway, Laura; Walker, Janet; Riba-Garcia, I.; Mohammed, S.; Deery, M.; Howard, J.; Dunkley, T.; Aebersold, R.; Kell, D.; Lilley, A.; Roepstorff, P.; Yates, J. R.; Brass, A.; Brown, Alistair James Petersen; Cash, Phillip; Gaskell, S.; Hubbard, S.; Oliver, S. G.

In: Nature Biotechnology, Vol. 21, No. 3, 03.2003, p. 247-254.

Research output: Contribution to journalArticle

Taylor, CF, Paton, NW, Garwood, KL, Kirby, PD, Stead, DA, Yin, Z, Deutsch, E, Selway, L, Walker, J, Riba-Garcia, I, Mohammed, S, Deery, M, Howard, J, Dunkley, T, Aebersold, R, Kell, D, Lilley, A, Roepstorff, P, Yates, JR, Brass, A, Brown, AJP, Cash, P, Gaskell, S, Hubbard, S & Oliver, SG 2003, 'A systematic approach to modeling, capturing, and disseminating proteomics experimental data', Nature Biotechnology, vol. 21, no. 3, pp. 247-254. https://doi.org/10.1038/nbt0303-247
Taylor, C. F. ; Paton, N. W. ; Garwood, K. L. ; Kirby, P. D. ; Stead, David Andrew ; Yin, Zhikang ; Deutsch, E. ; Selway, Laura ; Walker, Janet ; Riba-Garcia, I. ; Mohammed, S. ; Deery, M. ; Howard, J. ; Dunkley, T. ; Aebersold, R. ; Kell, D. ; Lilley, A. ; Roepstorff, P. ; Yates, J. R. ; Brass, A. ; Brown, Alistair James Petersen ; Cash, Phillip ; Gaskell, S. ; Hubbard, S. ; Oliver, S. G. / A systematic approach to modeling, capturing, and disseminating proteomics experimental data. In: Nature Biotechnology. 2003 ; Vol. 21, No. 3. pp. 247-254.
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