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Advanced query mechanisms for biological databases

I M Chen1, A S Kosky, V M Markowitz

  • 1Bioinformatics Systems Division, Gene Logic Inc., Berkeley, CA 94704, USA.

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|October 23, 1998
PubMed
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This study introduces new tools for biological database exploration, enabling intuitive ad-hoc querying across diverse data sources without needing complex query language knowledge. These tools simplify access to biological data, enhancing research accessibility.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Database Management

Background:

  • Current biological database interfaces are restrictive, using fixed forms or complex query languages.
  • These systems lack integration for application-specific complex biological data (e.g., DNA, proteins).
  • Users face challenges in querying heterogeneous data without deep technical knowledge.

Purpose of the Study:

  • To develop generic tools for flexible and uniform exploration of biological databases.
  • To provide intuitive interfaces for ad-hoc querying across heterogeneous data.
  • To integrate operations on complex biological data within query interfaces.

Main Methods:

  • Utilized the Object-Protocol Model (OPM) framework.
  • Developed a Java graphical query construction tool with automatic Web form generation.

Related Experiment Videos

  • Implemented query processors for complex objects and heterogeneous databases.
  • Created utilities for automatic HTML result page generation.

    • Main Results:

    • Introduced tools supporting interactive exploration of biological databases.
    • Enabled uniform querying via common data models, formats, and notations.
    • Facilitated ad-hoc queries across multiple heterogeneous databases and file systems.
    • Generated browsable HTML query results.

    Conclusions:

    • The developed tools overcome limitations of traditional interfaces.
    • Users can formulate complex queries intuitively without understanding underlying data models or languages.
    • Enhanced accessibility and flexibility for biological data exploration and research.