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Visualization Multi-Pipeline for Communicating Biology.

Peter Mindek, David Kouril, Johannes Sorger

    IEEE Transactions on Visualization and Computer Graphics
    |September 4, 2017
    PubMed
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    This study introduces a novel system for biology communication, creating interactive visualizations from diverse biological data for various devices. This facilitates real-time data updates and efficient dissemination of scientific discoveries.

    Area of Science:

    • Bioinformatics
    • Scientific Visualization
    • Computational Biology

    Background:

    • Biological discoveries are often communicated through static, manually created illustrations.
    • Traditional illustrations are time-consuming to update with new data and lack interactivity.
    • Disseminating updated biological information to users is often slow and inefficient.

    Purpose of the Study:

    • To develop a system for real-time, interactive visualization of heterogeneous biological data.
    • To overcome the limitations of traditional static illustrations in communicating biological discoveries.
    • To enable efficient and scalable dissemination of biological insights across diverse user devices.

    Main Methods:

    • A pipeline was developed to integrate and pre-process heterogeneous biological datasets.

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  • Data transformations generate real-time, interactive visual representations inspired by scientific illustrations.
  • Visualizations are rendered using a system with a desktop application and a scalable remote-rendering server.

    • Main Results:

    • The system successfully integrates diverse biological datasets into dynamic visualizations.
    • Interactive, real-time visual representations are generated, overcoming the limitations of static figures.
    • The remote-rendering server demonstrates scalability for multi-user, multi-GPU environments.

    Conclusions:

    • The proposed system enhances biology communication by providing interactive, up-to-date visualizations.
    • It supports the integration of heterogeneous data for a comprehensive understanding of biological knowledge.
    • The system's scalability ensures efficient public dissemination of biological discoveries across various platforms.