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Related Experiment Videos

Single nucleotide polymorphism hunting in cyberspace

Z Gu1, L Hillier, P Y Kwok

  • 1Division of Dermatology, Washington University School of Medicine, St. Louis, Missouri 63110, USA.

Human Mutation
|September 23, 1998
PubMed
Summary
This summary is machine-generated.

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Public DNA sequence databases offer an efficient way to discover gene-associated single nucleotide polymorphisms (SNPs). Computer screening of expressed sequence tags (ESTs) and genomic data allows cost-effective development of informative SNP markers.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Large-scale sequencing projects have generated vast amounts of human DNA sequence data.
  • Public databases like Genbank now contain millions of expressed sequence tags (ESTs) and genomic DNA sequences.
  • These databases represent a rich resource for identifying genetic variations.

Purpose of the Study:

  • To highlight the utility of public DNA sequence databases for discovering single nucleotide polymorphisms (SNPs).
  • To demonstrate the efficiency and cost-effectiveness of using computational methods for SNP identification.
  • To emphasize the value of public data access for advancing human genetic research.

Main Methods:

  • Comparing redundant expressed sequence tag (EST) sequences within public databases.

Related Experiment Videos

  • Analyzing overlapping genomic DNA clone sequences to identify variations.
  • Employing computer screening methods to detect informative single nucleotide polymorphisms (SNPs).

    • Main Results:

    • Public DNA sequence databases are a valuable source for identifying gene-associated and anonymous SNPs.
    • Computational screening of ESTs and genomic data enables efficient and cost-effective SNP marker development.
    • The process of finding DNA sequence variations is feasible with appropriate bioinformatics tools.

    Conclusions:

    • Publicly accessible human sequence data can be effectively mined for valuable SNP markers.
    • Investigator access to these databases facilitates the addition of biological value to generated sequence data.
    • This approach offers an efficient and cost-effective strategy for SNP discovery in human genetics.