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New flexible approaches for multiple sequence alignment

T Shibuya1, H Imai

  • 1Department of Information Science, Faculty of Science, University of Tokyo, Japan.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 1, 1997
PubMed
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This study introduces two novel methods for multiple sequence alignment, offering numerous suboptimal alignments and enabling parametric analysis. These approaches enhance biological significance beyond just optimal alignments for protein structure and phylogeny.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • Multiple sequence alignment (MSA) is crucial for protein structure prediction and phylogenetic inference.
  • Optimal alignments may not always reflect biological significance due to fixed scoring criteria.
  • Investigating suboptimal and parametrically varied alignments is essential for deeper biological insights.

Purpose of the Study:

  • To develop flexible and efficient methods for addressing limitations in traditional MSA.
  • To enable the exploration of suboptimal alignments and the impact of parameter variations in MSA.
  • To improve the biological relevance of MSA findings in molecular biology.

Main Methods:

  • Enumeration of suboptimal alignments using Eppstein algorithm and an efficient algorithm for necessary alignments.

Related Experiment Videos

  • Parametric analysis techniques for multiple sequence alignment problems.
  • Experimental validation using diverse protein sequence datasets.
  • Main Results:

    • Demonstrated feasibility of enumerating necessary suboptimal alignments for MSA.
    • Developed and tested methods for parametric multiple sequence alignment.
    • Evaluated the efficiency and properties of the proposed algorithms on real protein sequences.

    Conclusions:

    • The proposed methods offer significant improvements for exploring biological significance in MSA.
    • Suboptimal and parametric analyses provide valuable alternatives to solely optimal alignments.
    • These advancements enhance the utility of MSA in fields like structural biology and phylogenetics.