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Related Experiment Videos

Aligning biological sequences on distributed bus networks: a divisible load scheduling approach.

Wong Han Min1, Bharadwaj Veeravalli

  • 1Data Stage Institute, Agency for Science Technology and Research, Singapore. Wong_Han_Min@dsi.a-star.edu.sg

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
|December 29, 2005
PubMed
Summary

This study introduces a novel multiprocessor strategy using divisible load theory (DLT) to minimize biological sequence alignment time. The approach optimizes task partitioning for faster, accurate sequence comparisons, even on slow networks.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Parallel Computing

Background:

  • Biological sequence comparison is computationally intensive.
  • Existing methods may not scale efficiently for large datasets.
  • Divisible Load Theory (DLT) offers a framework for parallel processing on distributed systems.

Purpose of the Study:

  • To design a multiprocessor strategy for biological sequence comparison using DLT.
  • To minimize the total processing time for sequence alignment.
  • To adapt DLT for the unique computational characteristics of biological sequence alignment algorithms.

Main Methods:

  • Employed Divisible Load Theory (DLT) for task partitioning.
  • Considered computational speeds of nodes and network communication.

Related Experiment Videos

  • Developed strategies for heterogeneous, homogeneous, and slow networks.
  • Incorporated a post-processing phase for exact alignment.
  • Utilized a multi-installment strategy for enhanced parallelism.

    • Main Results:

    • Achieved minimum processing time for biological sequence alignment.
    • Derived closed-form solutions for various network configurations.
    • Proposed heuristic strategies for near-optimal solutions on slow networks.
    • Demonstrated effectiveness using real-life DNA samples (mouse and human mitochondria).

    Conclusions:

    • The DLT-based multiprocessor strategy effectively minimizes biological sequence alignment time.
    • The strategy is adaptable to different network conditions and can be extended to multi-sequence alignment.
    • This work represents the first application of DLT to biological sequence alignment, offering significant performance improvements.