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Related Experiment Videos

Data exploration tools for the Gene Ontology database.

Elizabeth Shoop1, Paulo Casaes, Getiria Onsongo

  • 1Mathematics and Computer Science Department, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105, USA. shoop@macalester.edu

Bioinformatics (Oxford, England)
|July 24, 2004
PubMed
Summary
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New tools, GoGet and GoView, enhance biological data exploration. These systems allow biologists to query the Gene Ontology (GO) database and visualize complex ontology graphs for deeper biological insights.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The Gene Ontology (GO) database is a critical resource for understanding gene and protein functions.
  • Biologists require improved tools to effectively query and explore the complex structure of the GO database.
  • Existing methods for querying and visualizing GO data can be cumbersome for large datasets.

Purpose of the Study:

  • To develop novel computational tools for querying and visualizing the Gene Ontology.
  • To enable biologists to ask complex, biologically relevant questions of the GO database.
  • To facilitate the exploration of large ontology graphs in context with detailed term information.

Main Methods:

  • Development of GoGet, a Java 2 Enterprise Edition-based query tool with a user-friendly interface.

Related Experiment Videos

  • Development of GoView, a Java 2 Enterprise Edition-based tool for visualizing directed acyclic graph structures of ontologies.
  • Integration of GoGet and GoView for coordinated data retrieval and visualization.

    • Main Results:

    • GoGet allows users to formulate specific biological queries, such as identifying proteins involved in specific pathways or filtering gene products by species.
    • Query results can be presented in a collapsed tabular format, simplifying the analysis of large datasets.
    • GoView provides interactive visualization of GO structures, allowing users to explore relationships between terms.
    • The coordinated system enables seamless transfer of results between GoGet and GoView for integrated analysis.

    Conclusions:

    • GoGet and GoView significantly improve biologists' ability to interact with and understand the Gene Ontology.
    • These tools empower researchers and students to formulate and answer complex biological questions more efficiently.
    • The provided web application system offers accessible and powerful methods for GO database exploration.