A fast algorithm for determining the best combination of local alignments to a query sequence

<p>Abstract</p> <p>Background</p> <p>Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or amino acids are in the same order in both sequences. Recombination...

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Main Authors: Wagner Andreas, Conant Gavin C
Format: Article
Language:English
Published: BMC 2004-05-01
Series:BMC Bioinformatics
Subjects:
Online Access:http://www.biomedcentral.com/1471-2105/5/62
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spelling doaj-4becf3acfb9a498796da8272c5b1fdad2020-11-24T21:44:40ZengBMCBMC Bioinformatics1471-21052004-05-01516210.1186/1471-2105-5-62A fast algorithm for determining the best combination of local alignments to a query sequenceWagner AndreasConant Gavin C<p>Abstract</p> <p>Background</p> <p>Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or amino acids are in the same order in both sequences. Recombination perturbs this order. An algorithm that can reconstruct sequence similarity despite rearrangement would be helpful for reconstructing the evolutionary history of recombined sequences.</p> <p>Results</p> <p>We propose a graph-based algorithm for combining multiple local alignments to a query sequence into the single combination of alignments that either covers the maximal portion of the query or results in the single highest alignment score to the query. This algorithm can help study the process of genome rearrangement, improve functional gene annotation, and reconstruct the evolutionary history of recombined proteins. The algorithm takes <it>O</it>(<it>n</it><sup>2</sup>) time, where <it>n </it>is the number of local alignments considered.</p> <p>Conclusions</p> <p>We discuss two example applications of the algorithm. The algorithm is able to provide useful reconstructions of the metazoan mitochondrial genome. It is also able to increase the percentage of a query sequence's amino acid residues for which similar stretches of amino acids can be found in sequence databases.</p> http://www.biomedcentral.com/1471-2105/5/62local alignmentalignment combination
collection DOAJ
language English
format Article
sources DOAJ
author Wagner Andreas
Conant Gavin C
spellingShingle Wagner Andreas
Conant Gavin C
A fast algorithm for determining the best combination of local alignments to a query sequence
BMC Bioinformatics
local alignment
alignment combination
author_facet Wagner Andreas
Conant Gavin C
author_sort Wagner Andreas
title A fast algorithm for determining the best combination of local alignments to a query sequence
title_short A fast algorithm for determining the best combination of local alignments to a query sequence
title_full A fast algorithm for determining the best combination of local alignments to a query sequence
title_fullStr A fast algorithm for determining the best combination of local alignments to a query sequence
title_full_unstemmed A fast algorithm for determining the best combination of local alignments to a query sequence
title_sort fast algorithm for determining the best combination of local alignments to a query sequence
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2004-05-01
description <p>Abstract</p> <p>Background</p> <p>Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or amino acids are in the same order in both sequences. Recombination perturbs this order. An algorithm that can reconstruct sequence similarity despite rearrangement would be helpful for reconstructing the evolutionary history of recombined sequences.</p> <p>Results</p> <p>We propose a graph-based algorithm for combining multiple local alignments to a query sequence into the single combination of alignments that either covers the maximal portion of the query or results in the single highest alignment score to the query. This algorithm can help study the process of genome rearrangement, improve functional gene annotation, and reconstruct the evolutionary history of recombined proteins. The algorithm takes <it>O</it>(<it>n</it><sup>2</sup>) time, where <it>n </it>is the number of local alignments considered.</p> <p>Conclusions</p> <p>We discuss two example applications of the algorithm. The algorithm is able to provide useful reconstructions of the metazoan mitochondrial genome. It is also able to increase the percentage of a query sequence's amino acid residues for which similar stretches of amino acids can be found in sequence databases.</p>
topic local alignment
alignment combination
url http://www.biomedcentral.com/1471-2105/5/62
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