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Comprehensive study on iterative algorithms of multiple sequence alignment

M Hirosawa1, Y Totoki, M Hoshida

  • 1Institute for New Generation Computer Technology, (ICOT), Tokyo, Japan.

Computer Applications in the Biosciences : CABIOS
|February 1, 1995
PubMed
Summary
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Iterative multiple sequence alignment methods improve accuracy, especially for low-similarity sequences. A tree-based iterative approach refines alignments, and a new partitioning technique speeds up the process.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Multiple sequence alignment (MSA) is crucial in biosciences.
  • Traditional tree-based algorithms struggle with low sequence similarity and cannot correct alignment errors.
  • Iterative algorithms offer improved alignment quality by refining partial alignments.

Purpose of the Study:

  • To comprehensively compare various iterative multiple sequence alignment algorithms.
  • To evaluate the effectiveness of a tree-based iterative method for MSA.
  • To introduce a novel technique for reducing the execution time of iterative algorithms.

Main Methods:

  • Comparison of different iterative MSA algorithms.
  • Implementation and analysis of a tree-based iterative refinement strategy.

Related Experiment Videos

  • Development of a tree-dependent, restricted partitioning technique.

    • Main Results:

    • Iterative refinement significantly enhances MSA quality, particularly for low-similarity sequences.
    • A tree-based iterative method demonstrates remarkable performance improvements.
    • The proposed partitioning technique efficiently reduces computational time for iterative algorithms.

    Conclusions:

    • Iterative strategies, especially tree-based ones, are superior for accurate multiple sequence alignment.
    • The developed partitioning method offers a practical solution for accelerating iterative MSA.
    • These advancements are vital for improving biological sequence analysis in bioinformatics.