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ORI-GENE: gene classification based on the evolutionary tree.

H Mizuno1, Y Tanaka, K Nakai

  • 1Institute of Biological Sciences, University of Tsukuba, 1-1-1 Ten-nodai, Tsukuba, Ibaraki 305-8572, Japan. hideaki.mizuno@roche.com

Bioinformatics (Oxford, England)
|March 10, 2001
PubMed
Summary

A new computational tool, ORI-GENE, aids in understanding gene function by analyzing evolutionary patterns from sequence homology searches. It helps classify newly discovered genes from genome projects.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Genome projects generate vast amounts of sequence data for genes with unknown functions.
  • Current methods for inferring gene function via sequence homology do not fully utilize available data.
  • There is a need for advanced tools to extract more biological insights from homology searches.

Purpose of the Study:

  • To develop a computational tool for analyzing sequence homology search results.
  • To leverage evolutionary perspectives for understanding new gene functions.
  • To improve the screening and classification of genes identified in genome analysis.

Main Methods:

  • Development of a computational tool named ORI-GENE with a graphical interface.
  • Analysis of sequence homology search outputs to identify gene distribution patterns across species.

Related Experiment Videos

  • Mapping gene distribution patterns onto a phylogenetic tree.

    • Main Results:

    • ORI-GENE identifies species with similar genes and visualizes their distribution on a phylogenetic tree.
    • The tool infers the propagation history of genes across species.
    • ORI-GENE predicts the origin of genes and classifies them based on evolutionary acquisition.

    Conclusions:

    • ORI-GENE provides an effective method for screening and classifying new genes from genomic data.
    • The tool enhances the biological information extracted from homology searches by incorporating evolutionary context.
    • Utilizing evolutionary information aids in understanding gene clustering and origins across species.