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PROTICdb: a web-based application to store, track, query, and compare plant proteome data.

Hélène Ferry-Dumazet1, Gwenn Houel, Pierre Montalent

  • 1Centre de Bioinformatique de Bordeaux, Université Victor Segalen Bordeaux 2, France.

Proteomics
|April 23, 2005
PubMed
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PROTICdb is a web application for storing and analyzing plant proteome data from 2-D PAGE and mass spectrometry. It aids in tracking experiments and building a knowledge base for data interpretation, supporting plant proteomic research.

Area of Science:

  • Proteomics
  • Bioinformatics
  • Plant Science

Background:

  • Plant proteome analysis generates large datasets requiring specialized storage and analysis tools.
  • Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS) are key techniques for plant proteomic studies.
  • Effective data management is crucial for interpreting complex proteomic information.

Purpose of the Study:

  • To introduce PROTICdb, a web-based application for managing and analyzing plant proteome data.
  • To facilitate the storage, tracking, and querying of proteomic experimental information from sample to identification.
  • To create an integrated knowledge base supporting the interpretation of proteomic data, including allelic variants and post-translational modifications.

Main Methods:

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  • Utilizes a relational database (Oracle or PostgreSQL) for data storage.
  • Accommodates data input via uploading outputs from image analysis and MS identification software.
  • Provides web forms for manual data entry and a graphical interface for querying and comparing 2-D PAGE annotated maps.
  • Integrates links to external databases and allows export of quantitative data for statistical analysis.

    • Main Results:

    • PROTICdb enables comprehensive storage and analysis of plant proteome data.
    • The application supports detailed tracking of proteomic experiments and facilitates data querying.
    • It offers tools for integrating diverse information sources to enhance data interpretation.
    • Quantitative data can be readily exported for statistical examination.

    Conclusions:

    • PROTICdb provides a valuable platform for plant proteomic research by centralizing data management and analysis.
    • The application enhances the interpretation of proteomic data through integrated knowledge bases and query functionalities.
    • PROTICdb is freely available, promoting wider accessibility and collaboration in plant proteomics.