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Parasite genome databases and web-based resources.

Christiane Hertz-Fowler1, Neil Hall

  • 1Pathogen Sequencing Unit, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, UK.

Methods in Molecular Biology (Clifton, N.J.)
|May 22, 2004
PubMed
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Researchers can access vital parasite genomics data through centralized online repositories. This overview highlights key databases like GeneDB and PlasmoDB for biological research.

Area of Science:

  • Genomics
  • Bioinformatics
  • Parasitology

Background:

  • High-throughput sequencing and omics technologies generate vast biological data.
  • These data are crucial for gene discovery, expression, and functional analysis in various organisms, including parasites.
  • Researchers increasingly rely on centralized online data repositories to supplement experimental work.

Purpose of the Study:

  • To provide an overview of essential resources for researchers in parasite genomics and biology.
  • To highlight publicly available nucleotide, protein sequence, and domain databases.
  • To focus on parasite genome projects and their associated web-based resources.

Main Methods:

  • Reviewing publicly available nucleotide and protein sequence databases.

Related Experiment Videos

  • Examining parasite genome projects and associated web resources.
  • Detailing specific databases such as GeneDB, PlasmoDB, and TIGRdb, including their scope and data retrieval tools.

    • Main Results:

    • Identification of numerous publicly available nucleotide and protein sequence databases.
    • Listing of current parasite sequencing projects with relevant web addresses.
    • In-depth description of GeneDB, PlasmoDB, and TIGRdb, emphasizing their integrated data and querying tools.

    Conclusions:

    • Centralized data repositories are indispensable for modern parasite genomics research.
    • Web-based resources and specialized databases facilitate access to and analysis of complex genomic data.
    • GeneDB, PlasmoDB, and TIGRdb are key resources for querying and retrieving integrated parasite genomic and biological datasets.