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MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract bio...

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Detalles Bibliográficos
Autores principales: Katoh, Kazutaka, Rozewicki, John, Yamada, Kazunori D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781576/
https://www.ncbi.nlm.nih.gov/pubmed/28968734
http://dx.doi.org/10.1093/bib/bbx108
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author Katoh, Kazutaka
Rozewicki, John
Yamada, Kazunori D
author_facet Katoh, Kazutaka
Rozewicki, John
Yamada, Kazunori D
author_sort Katoh, Kazutaka
collection PubMed
description This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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spelling pubmed-67815762019-10-18 MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization Katoh, Kazutaka Rozewicki, John Yamada, Kazunori D Brief Bioinform Paper This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs. Oxford University Press 2017-09-06 /pmc/articles/PMC6781576/ /pubmed/28968734 http://dx.doi.org/10.1093/bib/bbx108 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Paper
Katoh, Kazutaka
Rozewicki, John
Yamada, Kazunori D
MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title_full MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title_fullStr MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title_full_unstemmed MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title_short MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization
title_sort mafft online service: multiple sequence alignment, interactive sequence choice and visualization
topic Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781576/
https://www.ncbi.nlm.nih.gov/pubmed/28968734
http://dx.doi.org/10.1093/bib/bbx108
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