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Open Reading Frame Phylogenetic Analysis on the Cloud

Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather...

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Detalles Bibliográficos
Autores principales: Hung, Che-Lun, Lin, Chun-Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647537/
https://www.ncbi.nlm.nih.gov/pubmed/23671843
http://dx.doi.org/10.1155/2013/614923
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author Hung, Che-Lun
Lin, Chun-Yuan
author_facet Hung, Che-Lun
Lin, Chun-Yuan
author_sort Hung, Che-Lun
collection PubMed
description Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus.
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spelling pubmed-36475372013-05-13 Open Reading Frame Phylogenetic Analysis on the Cloud Hung, Che-Lun Lin, Chun-Yuan Int J Genomics Research Article Phylogenetic analysis has become essential in researching the evolutionary relationships between viruses. These relationships are depicted on phylogenetic trees, in which viruses are grouped based on sequence similarity. Viral evolutionary relationships are identified from open reading frames rather than from complete sequences. Recently, cloud computing has become popular for developing internet-based bioinformatics tools. Biocloud is an efficient, scalable, and robust bioinformatics computing service. In this paper, we propose a cloud-based open reading frame phylogenetic analysis service. The proposed service integrates the Hadoop framework, virtualization technology, and phylogenetic analysis methods to provide a high-availability, large-scale bioservice. In a case study, we analyze the phylogenetic relationships among Norovirus. Evolutionary relationships are elucidated by aligning different open reading frame sequences. The proposed platform correctly identifies the evolutionary relationships between members of Norovirus. Hindawi Publishing Corporation 2013 2013-03-31 /pmc/articles/PMC3647537/ /pubmed/23671843 http://dx.doi.org/10.1155/2013/614923 Text en Copyright © 2013 C.-L. Hung and C.-Y. Lin. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hung, Che-Lun
Lin, Chun-Yuan
Open Reading Frame Phylogenetic Analysis on the Cloud
title Open Reading Frame Phylogenetic Analysis on the Cloud
title_full Open Reading Frame Phylogenetic Analysis on the Cloud
title_fullStr Open Reading Frame Phylogenetic Analysis on the Cloud
title_full_unstemmed Open Reading Frame Phylogenetic Analysis on the Cloud
title_short Open Reading Frame Phylogenetic Analysis on the Cloud
title_sort open reading frame phylogenetic analysis on the cloud
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647537/
https://www.ncbi.nlm.nih.gov/pubmed/23671843
http://dx.doi.org/10.1155/2013/614923
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