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Related Experiment Videos

The PlantsP and PlantsT Functional Genomics Databases.

Jason H Tchieu1, Fariba Fana, J Lynn Fink

  • 1San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0537, USA.

Nucleic Acids Research
|January 10, 2003
PubMed
Summary

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PlantsP and PlantsT are curated plant databases offering insights into plant phosphoproteins and membrane transporters. These resources integrate sequence data with experimental findings, aiding molecular biology research.

Area of Science:

  • Plant molecular biology
  • Bioinformatics
  • Genomics

Background:

  • Plant phosphoproteins and membrane transporters are crucial for cellular processes.
  • Understanding their function and evolution is vital for plant science.
  • Existing resources may lack integrated experimental and sequence-derived data.

Purpose of the Study:

  • To present PlantsP and PlantsT, two curated plant-specific databases.
  • To provide comprehensive information on plant phosphoproteins (PlantsP) and membrane transporters (PlantsT).
  • To integrate sequence data with experimental functional-genomics data for enhanced understanding.

Main Methods:

  • Development of two distinct web interfaces (PlantsP and PlantsT) within a single database framework.
  • Curating sequence-derived information and experimental functional-genomics data.

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  • Incorporating data on T-DNA insertion mutants, mineral composition analysis (ICP-AES), motifs, domains, and literature-derived information.

    • Main Results:

    • PlantsP focuses on kinases and phosphatases, including knockout mutant data.
    • PlantsT focuses on membrane transport proteins, uniquely linking mineral composition data of mutants and wild-type strains.
    • Both databases offer expert-contributed information, literature data, and user annotation features.

    Conclusions:

    • PlantsP and PlantsT serve as valuable, integrated resources for plant molecular biology research.
    • These databases facilitate a deep understanding of individual genes and their products.
    • The user annotation feature promotes community-driven data enrichment.