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Distributed sequence alignment applications for the public computing architecture.

S Pellicer1, G Chen, K C C Chan

  • 1Department of Computer Science, Georgia State University, Atlanta, GA 30302-3965, USA. spellicer1@student.gsu.edu

IEEE Transactions on Nanobioscience
|March 13, 2008
PubMed
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Public computer architecture, using the Berkeley Open Infrastructure for Network Computing (BOINC), significantly speeds up bioinformatics tasks like BLAST. This distributed computing approach offers practical solutions for large-scale gene sequence alignment and data mining.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Distributed Computing

Background:

  • Public computer architecture offers a promising platform for complex bioinformatics problems.
  • Tools like Basic Local Alignment Search Tool (BLAST) are crucial for data mining and sequence alignment.

Purpose of the Study:

  • To implement and evaluate global gene sequence alignment and BLAST on the Berkeley Open Infrastructure for Network Computing (BOINC) platform.
  • To assess the runtime reduction and resource utilization of distributed computing for bioinformatics tasks.

Main Methods:

  • Implementation of gene sequence alignment and BLAST on the BOINC platform.
  • Comparison of runtime performance against theoretical sequential execution.
  • Analysis of memory aggregation capabilities in the distributed system.

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Main Results:

  • Achieved a runtime reduction factor of 1.15 for sequence alignment and 16.76 for BLAST.
  • The BOINC implementation leverages aggregated memory from participant nodes, overcoming single-system memory limitations.
  • Potential for more significant runtime reductions compared to practical sequential runs due to reduced I/O overhead.

Conclusions:

  • The BOINC platform provides a practical and efficient solution for grid- and cluster-scale bioinformatics computations.
  • Distributed computing architectures demonstrate significant potential for accelerating fundamental bioinformatics problems.
  • Despite communication overhead limitations, public computer architecture is a viable platform for current and future bioinformatics research.