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DEPD: a novel database for differentially expressed proteins.

Quan-Yuan He1, Jing Cao, Xiang-Hua Liu

  • 1College of Life Science, Hunan Normal University, Changsha 410081, People's Republic of China.

Bioinformatics (Oxford, England)
|July 16, 2005
PubMed
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The Differentially Expressed Protein Database (DEP D) offers a public platform for analyzing proteomics data. It contains over 3000 proteins from comparative studies, aiding biological and experimental insights.

Area of Science:

  • Proteomics
  • Bioinformatics
  • Data Mining

Background:

  • Comparative proteomics studies generate large datasets of differentially expressed proteins (DEPs).
  • A centralized, accessible platform is needed to manage and analyze this data.
  • The DEP D aims to consolidate and present information on DEPs from published literature.

Purpose of the Study:

  • To create a publicly available database for storing and analyzing comparative proteomics data.
  • To provide a user-friendly interface for querying and exploring differentially expressed proteins.
  • To facilitate data mining and functional analysis of DEPs.

Main Methods:

  • Manual extraction of protein information from published literature.
  • Inclusion of biological, experimental, and methodological details for each protein.

Related Experiment Videos

  • Development of a web interface with query and analysis tools.

    • Main Results:

    • The database contains information on over 3000 differentially expressed proteins.
    • Data includes comprehensive biological, experimental, and methodological context.
    • Integrated tools enable visualization and functional analysis of DEPs.

    Conclusions:

    • The DEP D serves as a valuable resource for the proteomics research community.
    • It simplifies data mining and enhances the understanding of protein expression patterns.
    • The platform supports efficient exploration of comparative proteomics study outputs.