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ISPIDER Central: an integrated database web-server for proteomics.

Jennifer A Siepen1, Khalid Belhajjame, Julian N Selley

  • 1Faculty of Life Sciences, University of Manchester, M13 9PT, UK.

Nucleic Acids Research
|April 29, 2008
PubMed
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This summary is machine-generated.

Integrating proteomic data is challenging due to format and accession variability. ISPIDER provides a unified search across major proteomic databases, enabling comprehensive analysis of mass spectrometry-based proteomics experiments.

Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Proteomic data integration is hindered by diverse formats, accessions, and repository services.
  • Existing proteomic databases lack unified search capabilities, complicating data retrieval and analysis.

Purpose of the Study:

  • To develop an integrated service for searching and accessing data from multiple leading proteomic repositories.
  • To overcome limitations in protein accession variability across different databases.

Main Methods:

  • Developed the ISPIDER Central Proteomic Database search service.
  • Integrated leading proteomic repositories: PRIDE, PepSeeker, PeptideAtlas, and Global Proteome Machine.
  • Utilized the European Bioinformatics Institute's Protein Identifier Cross-Reference (PICR) service for accession resolution.

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  • Implemented custom clients for viewing and integrating data, including Dasty2 for annotations.

    • Main Results:

    • ISPIDER offers novel search capabilities across disparate proteomic repositories.
    • The service successfully integrates protein and peptide identifications from mass spectrometry-based experiments.
    • PICR service effectively resolves protein accession number variability.
    • Custom clients provide enhanced visualization and integration with annotation servers.

    Conclusions:

    • ISPIDER provides the first truly integrated access to major proteomics repositories.
    • This service offers a unique solution for biologists analyzing mass spectrometry-based proteomics data.
    • Facilitates more comprehensive and efficient analysis of large-scale proteomic datasets.