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Related Experiment Videos

Profile sequence analysis and database searches on a transputer machine connected to a Macintosh computer

G Vogt1, P Argos

  • 1European Molecular Biology Laboratory, Heidelberg, Germany.

Computer Applications in the Biosciences : CABIOS
|February 1, 1993
PubMed
Summary

A new parallel computing implementation of Profilesearch enables fast protein sequence similarity searches. This user-friendly system offers efficient database searching using a PC front-end and dynamic programming alignment.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Parallel Computing

Background:

  • Protein sequence similarity searching is crucial for understanding protein function and evolution.
  • Traditional methods can be computationally intensive, limiting database search speed and accessibility.
  • Parallel computing offers a potential solution for accelerating these complex analyses.

Purpose of the Study:

  • To implement the Profilesearch algorithm on a parallel computing architecture.
  • To create a user-friendly interface for efficient protein sequence database searching.
  • To evaluate the performance and scalability of the parallel Profilesearch implementation.

Main Methods:

  • Developed a Profilesearch implementation utilizing a T800 transputer-based parallel computer.

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  • Integrated the parallel system with a Macintosh IIcx host computer for a user-friendly interface.
  • Employed standard dynamic programming techniques for sequence alignment.

    • Main Results:

    • Achieved significant speed improvements compared to a VAXstation 3200, even with a single transputer.
    • Demonstrated approximately linear speed increase with up to 21 transputers, indicating good scalability.
    • The system provides a cost-effective and fast solution for protein sequence similarity searches.

    Conclusions:

    • The parallel Profilesearch implementation offers a powerful and accessible tool for bioinformatics research.
    • The user-friendly interface and efficient performance facilitate rapid database searches for sequence similarities.
    • This approach enables quick identification of relationships between protein sequences and large databases.