Advertisement

Storing, Searching, and Disseminating Experimental Proteomics Data

  • Norman W. Paton
  • Andrew R. Jones
  • Chris Garwood
  • Kevin Garwood
  • Stephen Oliver
Chapter

Abstract

The chapter introduces the challenges of storing, sharing, and querying proteomics data caused by the complexity of the experimental techniques, and the speed with which the techniques evolve. Public proteome databases are difficult to develop and populate because of the range of data types and queries that must be supported, and the quantity of metadata required to validate results. There are several data standards under development that should alleviate some of the challenges, and databases that utilize the standards are becoming more widely supported. The chapter describes a model of a complete proteomics pipeline, including the metadata that should be captured to allow confidence to be placed on the results. Software is also required, which can produce data conforming to the standards and that can be used to query proteomics data repositories. The chapter outlines the requirements for software and presents two exemplars developed at the University of Manchester. Finally, there is a description of the likely future developments in standardization for proteomics.

Key Words

Proteomics mass spectrometry data standard database PEDRo Proteomics Standards Initiative 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Liebler DC. Introduction to Proteomics. Totowa: Humana Press; 2002.Google Scholar
  2. 2.
    Righetti PG, Castagna A, Herbert B, et al. Prefractionation techniques in proteome analysis. Proteomics 2003 Aug;3(8):1397–1407.PubMedCrossRefGoogle Scholar
  3. 3.
    Carr S, Aebersold R, Baldwin M, et al. Working Group on Publication Guidelines for Peptide and Protein Identification Data. The need for guidelines in publication of peptide and protein identification data: Working Group on Publication Guidelines for Peptide and Protein Identification Data. Mol Cell Proteomics 2004 Jun;3(6):531–533.PubMedCrossRefGoogle Scholar
  4. 4.
    Hoogland C, Mostaguir K, Sanchez JC, Hochstrasser DF, Appel RD. SWISS-2DPAGE, ten years later. Proteomic. 2004 Aug;4(8):2352–2356.CrossRefGoogle Scholar
  5. 5.
    Martens L, Hermjakob H, Jones P, et al. PRIDE: The proteomics identifications database. Proteomics 2005 Oct;5(13):3537–3545.PubMedCrossRefGoogle Scholar
  6. 6.
    Craig R, Cortens JP, Beavis RC. Open source system for analyzing, validating, and storing protein identification data. J Proteome Re. 2004 Nov–Dec; 3(6):1234–1242.CrossRefGoogle Scholar
  7. 7.
    Pedrioli PG, Eng JK, Hubley R, et al. A common open representation of mass spectrometry data and its application to proteomics research. Nature Biotechnol 2004 Nov;22(11):1459–1466.CrossRefGoogle Scholar
  8. 8.
    Garwood K, McLaughlin T, Garwood C, et al. PEDRo: a database for storing, searching and disseminating experimental proteomics data. BMC Genomics 2004 Sep 17;5(1):68.PubMedCrossRefGoogle Scholar
  9. 9.
    Taylor CF, Paton NW, Garwood KL, et al. A systematic approach to modeling, capturing, and disseminating proteomics experimental data. Nature Biotechnol 2003, Mar;21(3):247–254.CrossRefGoogle Scholar
  10. 10.
    Kapp EA, Schutz F, Connolly LM, et al. An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: sensitivity and specificity analysis. Proteomics 2005 Aug;5(13): 3475–3490.PubMedCrossRefGoogle Scholar
  11. 11.
    Garwood KL, Taylor CF, Runte KJ, et al. Pedro: a configurable data entry tool for XML. Bioinformatics 2004 Oct 12;20(15):2463–2465.PubMedCrossRefGoogle Scholar
  12. 12.
    Dunkley TP, Watson R, Griffin JL, et al. Localization of organelle proteins by isotope tagging (LOPIT). Mol Cell Proteomics 2004 Nov;3(11): 1128–1134.PubMedCrossRefGoogle Scholar
  13. 13.
    Ross PL, Huang YN, Marchese JN, et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 2004 Dec;3(12):1154–1169.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Norman W. Paton
    • 1
  • Andrew R. Jones
    • 1
  • Chris Garwood
    • 1
  • Kevin Garwood
    • 1
  • Stephen Oliver
    • 2
  1. 1.School of Computer ScienceUniversity of ManchesterManchesterUK
  2. 2.School of Life SciencesUniversity of ManchesterManchesterUK

Personalised recommendations