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Related Experiment Videos

Go!Poly: A gene-oriented polymorphism database.

G Zhang1, S Zhang, W Chen

  • 1Department of Medical Genetics, First Affiliated Hospital, West China College of Clinical Medicine, Sichuan University, Chengdu, People's Republic of China.

Human Mutation
|October 23, 2001
PubMed
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Go!Poly is a new gene-oriented database for human genetic variations. It simplifies finding gene-linked polymorphisms by integrating LocusLink and RefSeq data, aiding research into disease susceptibility and drug responses.

Area of Science:

  • Genetics
  • Bioinformatics
  • Genomics

Background:

  • Human genome polymorphisms are crucial for individual phenotypic differences, including disease susceptibility and drug responses.
  • Existing generalized databases struggle to provide easily accessible gene-related variation data.
  • There is a need for specialized databases to efficiently manage and retrieve human genetic variation information.

Purpose of the Study:

  • To develop Go!Poly, a gene-oriented polymorphism database for enhanced accessibility of human genetic variation data.
  • To utilize curated resources like LocusLink and RefSeq for accurate identification and positioning of nucleotide variations.
  • To facilitate the search and navigation of gene-linked polymorphism data.

Main Methods:

  • Go!Poly integrates data from LocusLink and RefSeq as standards for variation identification and positioning.

Related Experiment Videos

  • It extracts human gene-linked sequence variations (SNP, insertion-deletion, etc.) from diverse public resources (journals, HGBASE, dbSNP).
  • Polymorphism data is categorized by gene loci, using LocusLink reference sequences for positioning.

    • Main Results:

    • Go!Poly provides a gene-oriented directory of human polymorphism data.
    • It offers facilitated connections between sequence data, gene names, and biological information through LocusLink integration.
    • The database is designed for easy searching and navigation of genetic variation data.

    Conclusions:

    • Go!Poly addresses the challenge of finding gene-related variation data in large databases.
    • Its gene-centric approach and integration with LocusLink improve accessibility and usability for researchers.
    • Future enhancements include automated annotations and internal consistency checks, with a focus on incorporating Chinese scientific community data.