A Pairwise Alignment Algorithm for Long Sequences of High Similarity

Alignment algorithms are important in bioinformatics for comparing the similarity among sequences. The algorithm of Needleman–Wunsch is well known for globally aligning two sequences. However, this algorithm is unsuitable for sequences of long length. Many heuristic algorithms are proposed, such as...

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Autores principales: Lee, Chien-Tai, Peng, Sheng-Lung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123042/
http://dx.doi.org/10.1007/978-981-10-5508-9_27
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author Lee, Chien-Tai
Peng, Sheng-Lung
author_facet Lee, Chien-Tai
Peng, Sheng-Lung
author_sort Lee, Chien-Tai
collection PubMed
description Alignment algorithms are important in bioinformatics for comparing the similarity among sequences. The algorithm of Needleman–Wunsch is well known for globally aligning two sequences. However, this algorithm is unsuitable for sequences of long length. Many heuristic algorithms are proposed, such as BLAST and FASTA. However, they are still unsuitable for long sequences. In this paper, we study the alignment problem on highly similar sequences. By taking SARS viruses as an example, our result shows that our algorithm runs faster than Clustalx for aligning two SARS viruses. It implies that our algorithm is suitable for viruses of high similarity.
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spelling pubmed-71230422020-04-06 A Pairwise Alignment Algorithm for Long Sequences of High Similarity Lee, Chien-Tai Peng, Sheng-Lung Information and Communication Technology Article Alignment algorithms are important in bioinformatics for comparing the similarity among sequences. The algorithm of Needleman–Wunsch is well known for globally aligning two sequences. However, this algorithm is unsuitable for sequences of long length. Many heuristic algorithms are proposed, such as BLAST and FASTA. However, they are still unsuitable for long sequences. In this paper, we study the alignment problem on highly similar sequences. By taking SARS viruses as an example, our result shows that our algorithm runs faster than Clustalx for aligning two SARS viruses. It implies that our algorithm is suitable for viruses of high similarity. 2017-10-13 /pmc/articles/PMC7123042/ http://dx.doi.org/10.1007/978-981-10-5508-9_27 Text en © Springer Nature Singapore Pte Ltd. 2018 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
Lee, Chien-Tai
Peng, Sheng-Lung
A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title_full A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title_fullStr A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title_full_unstemmed A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title_short A Pairwise Alignment Algorithm for Long Sequences of High Similarity
title_sort pairwise alignment algorithm for long sequences of high similarity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7123042/
http://dx.doi.org/10.1007/978-981-10-5508-9_27
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