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Multiple Sequence Alignment

The multiple sequence alignment (MA) plays an important role in sequence analysis. However, it has been proven to be an NP-hard problem. This means the computation complexity of MSA increases exponentially with the number of sequences. The presented algorithms are mostly heuristic and many of them a...

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Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123353/
http://dx.doi.org/10.1007/978-3-540-74891-5_6
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collection PubMed
description The multiple sequence alignment (MA) plays an important role in sequence analysis. However, it has been proven to be an NP-hard problem. This means the computation complexity of MSA increases exponentially with the number of sequences. The presented algorithms are mostly heuristic and many of them are based on pairwise sequence alignment. Hence we begin with pairwise alignment of multiple sequences and discuss the topological space induced by pairwise alignment of multiple sequences, since different optimization criteria may lead to different results. We discuss several optimization indices here: the sum of pairs (SP); Shannon entropy; similarity rate and the rate of virtual symbols. Based on this discussion, we present a new multiple sequence alignment based on SPA called super multiple sequence alignment (SMA). We give a detailed description of the algorithm and compare it to some popular MA algorithms and find that it works well enough, especially with respect to speed. An example of SARS multiple sequence alignment is given at the end of this chapter.
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spelling pubmed-71233532020-04-06 Multiple Sequence Alignment Theory and Mathematical Methods for Bioinformatics Article The multiple sequence alignment (MA) plays an important role in sequence analysis. However, it has been proven to be an NP-hard problem. This means the computation complexity of MSA increases exponentially with the number of sequences. The presented algorithms are mostly heuristic and many of them are based on pairwise sequence alignment. Hence we begin with pairwise alignment of multiple sequences and discuss the topological space induced by pairwise alignment of multiple sequences, since different optimization criteria may lead to different results. We discuss several optimization indices here: the sum of pairs (SP); Shannon entropy; similarity rate and the rate of virtual symbols. Based on this discussion, we present a new multiple sequence alignment based on SPA called super multiple sequence alignment (SMA). We give a detailed description of the algorithm and compare it to some popular MA algorithms and find that it works well enough, especially with respect to speed. An example of SARS multiple sequence alignment is given at the end of this chapter. 2008 /pmc/articles/PMC7123353/ http://dx.doi.org/10.1007/978-3-540-74891-5_6 Text en © Springer-Verlag Berlin Heidelberg 2008 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Multiple Sequence Alignment
title Multiple Sequence Alignment
title_full Multiple Sequence Alignment
title_fullStr Multiple Sequence Alignment
title_full_unstemmed Multiple Sequence Alignment
title_short Multiple Sequence Alignment
title_sort multiple sequence alignment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123353/
http://dx.doi.org/10.1007/978-3-540-74891-5_6