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Related Experiment Videos

Applying a grid technology to protein structure predictor "ROKKY".

Kazutoshi Fujikawa1, Wenzhen Jin, Sung-Joon Park

  • 1Information Technology Center, Nara Institute of Science and Technology, Japan. fujikawa@itc.naist.jp

Studies in Health Technology and Informatics
|June 1, 2005
PubMed
Summary
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The High Throughput Computing (HTC) group developed a flexible system for protein structure prediction. This system was successfully applied to the ROKKY protein structure predictor, improving computational efficiency.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Structural Biology

Background:

  • Protein structure prediction is computationally intensive and often relies on trial-and-error.
  • The BioGrid project aims to enhance biological data analysis and computation.
  • High Throughput Computing (HTC) offers a solution for resource-demanding scientific tasks.

Purpose of the Study:

  • To describe the development of an HTC system for protein structure prediction.
  • To demonstrate the application of this HTC system to the ROKKY protein structure predictor.
  • To evaluate the efficiency of the HTC system in handling complex computational workflows.

Main Methods:

  • Development of a flexible workflow handling mechanism for HTC.
  • Integration of the HTC system with the ROKKY protein structure prediction tool.

Related Experiment Videos

  • Application of the system to large-scale protein structure prediction tasks.

    • Main Results:

    • The HTC system was successfully applied to the ROKKY protein structure predictor.
    • The system demonstrated efficient handling of the computational demands of protein structure prediction.
    • The workflow mechanism proved flexible for the specific requirements of ROKKY.

    Conclusions:

    • The developed HTC system is effective for protein structure prediction.
    • Applying HTC to tools like ROKKY can significantly improve computational resource utilization.
    • This approach offers a scalable solution for complex bioinformatics challenges.