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The UCSC Known Genes.

Fan Hsu1, W James Kent, Hiram Clawson

  • 1Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz Santa Cruz, CA 95064, USA. fanhsu@soe.ucsc.edu

Bioinformatics (Oxford, England)
|February 28, 2006
PubMed
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The University of California Santa Cruz Known Genes dataset provides comprehensive gene information for human, mouse, and rat, supporting key genomic programs. Analysis shows it offers high genomic and CDS coverage, though improvements are possible.

Area of Science:

  • Genomics
  • Proteomics
  • Bioinformatics

Background:

  • The UCSC Known Genes dataset is a crucial resource for genomic and proteomic research.
  • Accurate and comprehensive gene annotation is essential for understanding biological functions and disease mechanisms.

Purpose of the Study:

  • To describe the automated construction of the UCSC Known Genes dataset.
  • To detail the cross-referencing capabilities and information richness of the dataset.
  • To analyze and compare the genomic coverage of UCSC Known Genes with other major gene sets.

Main Methods:

  • Automated data processing using protein data from UniProt (Swiss-Prot/TrEMBL) and mRNA data from Genbank.
  • Development of extensive cross-references to other genomic and proteomic databases.

Related Experiment Videos

  • Comparative analysis of genomic and CDS coverage against RefSeq, Ensembl Genes, H-Invitational, and CCDS.

    • Main Results:

    • The UCSC Known Genes dataset is available for human, mouse, and rat genomes, with detailed information pages and extensive links.
    • The dataset supports key UCSC bioinformatics tools like the Genome Browser and Proteome Browser.
    • UCSC Known Genes demonstrates superior genomic and CDS coverage compared to other major human and mouse gene sets, yet all sets show potential for enhancement.

    Conclusions:

    • The UCSC Known Genes dataset is a valuable, comprehensive resource for the scientific community.
    • The dataset's high coverage and integration capabilities facilitate advanced genomic and proteomic analyses.
    • Continuous improvement of gene annotation resources is necessary for advancing biological research.