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Novel techniques for visualising biological information

A J Robinson1, T P Flores

  • 1EMBL Outstation-The European Bioinformatics Institute, Cambridge, UK. alan@ebi.ac.uk, tflores@ebi.ac.uk

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|January 1, 1997
PubMed
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Bioinformatics faces challenges with increasing biological database size and complexity. This research develops advanced visualization and distributed object technologies to extract valuable information, creating a new generation of bioinformatics tools.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Visualization

Background:

  • The exponential growth of biological databases presents significant challenges for data analysis and information extraction.
  • Existing bioinformatics tools often struggle with the scale and complexity of modern biological data.

Purpose of the Study:

  • To develop and utilize advanced visualization methods and distributed object technologies for extracting novel information from large biological databases.
  • To enhance user interaction and data navigation within complex biological information spaces.

Main Methods:

  • Employing advanced visualization techniques for intuitive data browsing and querying.
  • Utilizing distributed object technologies for seamless communication between applications and remote databases.

Related Experiment Videos

  • Developing reusable software components using platform-independent, object-oriented programming languages.

    • Main Results:

    • Demonstrated the effectiveness of visualization and distributed object technologies in managing and analyzing large-scale biological data.
    • Facilitated the creation of user-friendly interfaces for intuitive navigation of complex data.
    • Enabled the development of powerful, modular bioinformatics applications through component-based architecture.

    Conclusions:

    • Advanced visualization and distributed object technologies are crucial for addressing the challenges posed by burgeoning biological databases.
    • The widget and object-oriented approach accelerates application development, allowing more focus on data analysis.
    • This paradigm shift enables the construction of a new generation of powerful and interconnected bioinformatics tools.