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A distributed approach for a multiple sequence alignment algorithm using a parallel virtual machine.

Heitor Lopes1, Guilherme Moritz

  • 1Bioinformatics Laboratory/CPGEI, Federal Center for Technological Education of Parana, Av. 7 de setembro, 3165 - 80230-901 Curitiba, Brazil hslopes@cpgei.cefetpr.br.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|February 7, 2007
PubMed
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This study presents a parallel processing method for the ClustalW multiple sequence alignment algorithm. The approach enhances computational biology by efficiently handling large-scale protein sequence comparisons.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Algorithm Development

Background:

  • Multiple sequence alignment is crucial for understanding protein evolution and function.
  • Existing algorithms can be computationally intensive for large datasets.
  • Parallel processing offers a potential solution for accelerating these analyses.

Purpose of the Study:

  • To develop and evaluate a methodology for parallel processing of the ClustalW algorithm.
  • To demonstrate the efficiency and scalability of a distributed system for multiple sequence alignment.
  • To provide an advantage for large-scale protein sequence comparison tasks.

Main Methods:

  • Implementation of a distributed system for parallel execution of the ClustalW algorithm.
  • Detailed description of system modules, focusing on parallel dynamic programming.

Related Experiment Videos

  • Performance and scalability evaluation through extensive experiments.

    • Main Results:

    • The proposed method demonstrates efficient parallel processing capabilities.
    • The system shows significant advantages for large-scale multiple protein sequence alignment.
    • Scalability was confirmed through experimental validation.

    Conclusions:

    • The developed methodology offers an efficient and advantageous solution for large-scale multiple sequence alignment.
    • Parallel processing of ClustalW is feasible and beneficial in networked environments.
    • This work contributes to advancing computational biology tools for sequence analysis.