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A Practical Guide to Phylogenetics for Nonexperts
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Published on: February 5, 2014

An efficient algorithm for local sequence alignment.

Waqar Haque1, Alex Aravind, Bharath Reddy

  • 1Computer Science Program, University of Northern British Columbia, Canada, V2N 4Z9.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 24, 2009
PubMed
Summary

We developed a novel DNA sequence alignment algorithm that balances speed and sensitivity. This method uses suffix trees and mismatch seeds for efficient pairwise sequence comparison.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA pairwise sequence alignment is crucial in bioinformatics.
  • Existing algorithms present a trade-off between speed and sensitivity.
  • There is a need for alignment tools that are both fast and sensitive.

Purpose of the Study:

  • To introduce a new DNA sequence alignment algorithm.
  • To achieve a balance between speed and sensitivity in sequence alignment.
  • To improve upon existing methods for large-scale sequence comparison.

Main Methods:

  • Constructing suffix trees for both DNA sequences.
  • Using maximum matching substrings to initiate alignment.
  • Employing mismatch seeds to enhance sensitivity and speed in later stages.
  • Testing the algorithm on large random sequences (up to 500,000 bp) and the Rosetta dataset.

Main Results:

  • The new algorithm demonstrates a favorable combination of speed and relative sensitivity.
  • The use of suffix trees and mismatch seeds contributes to efficient alignment.
  • Performance was validated on extensive datasets.

Conclusions:

  • The developed algorithm offers a promising solution for fast and sensitive DNA sequence alignment.
  • This approach can be valuable for large-scale genomic analyses.
  • Further research can explore optimizations and applications of this method.