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Related Experiment Videos

Multiple protein sequence alignment using double-dynamic programming.

W R Taylor1, G Saelensminde, I Eidhammer

  • 1Division of Mathematical Biology, National Institute for Medical Research, London, UK. w_taylor@nimr.mrc.ac.uk

Computers & Chemistry
|January 22, 2000
PubMed
Summary
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This study introduces a novel multiple sequence alignment method using double dynamic programming (DDP). The DDP approach effectively reconciles pairwise alignment inconsistencies, yielding results comparable to standard progressive methods in a single pass.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Bioinformatics

Background:

  • Multiple sequence alignment (MSA) is crucial for understanding protein evolution and function.
  • Existing MSA methods face challenges in reconciling pairwise alignment inconsistencies.
  • Previous applications of double dynamic programming (DDP) focused on structural constraints.

Purpose of the Study:

  • To develop a novel MSA method based on the DDP algorithm.
  • To address and reconcile inconsistencies in combining pairwise alignments into a multiple alignment.
  • To evaluate the efficiency and accuracy of the new DDP-based MSA method.

Main Methods:

  • The method employs double dynamic programming (DDP) to reconcile pairwise alignment inconsistencies.

Related Experiment Videos

  • Low-level alignments (paths) are summed into a matrix for a high-level alignment.
  • Pairwise alignment results are combined in a multiple sequence alignment program.
  • Iterative refinement using selected constraints was explored but found unnecessary.
  • Main Results:

    • The DDP-based method effectively reconciles inconsistencies from pairwise alignments.
    • A single-pass application of the method produced results comparable to standard progressive alignment.
    • The iterative refinement step did not improve alignment quality.

    Conclusions:

    • The novel DDP-based method offers an efficient and accurate approach to multiple sequence alignment.
    • The method successfully overcomes limitations of combining pairwise alignments.
    • Future applications in structural bioinformatics and related fields are promising.