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MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database
SUMMARY: We present MIDORI server, a user-friendly web platform that uses a curated reference dataset, MIDORI, for high throughput taxonomic classification of unknown metazoan mitochondrial-encoded gene sequences. Currently three methods of taxonomic assignments: RDP Classifier, SPINGO and SINTAX, a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198853/ https://www.ncbi.nlm.nih.gov/pubmed/29878054 http://dx.doi.org/10.1093/bioinformatics/bty454 |
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author | Leray, Matthieu Ho, Shian-Lei Lin, I-Jeng Machida, Ryuji J |
author_facet | Leray, Matthieu Ho, Shian-Lei Lin, I-Jeng Machida, Ryuji J |
author_sort | Leray, Matthieu |
collection | PubMed |
description | SUMMARY: We present MIDORI server, a user-friendly web platform that uses a curated reference dataset, MIDORI, for high throughput taxonomic classification of unknown metazoan mitochondrial-encoded gene sequences. Currently three methods of taxonomic assignments: RDP Classifier, SPINGO and SINTAX, are implemented. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at {http://reference-midori.info/server.php}. |
format | Online Article Text |
id | pubmed-6198853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61988532018-10-26 MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database Leray, Matthieu Ho, Shian-Lei Lin, I-Jeng Machida, Ryuji J Bioinformatics Applications Notes SUMMARY: We present MIDORI server, a user-friendly web platform that uses a curated reference dataset, MIDORI, for high throughput taxonomic classification of unknown metazoan mitochondrial-encoded gene sequences. Currently three methods of taxonomic assignments: RDP Classifier, SPINGO and SINTAX, are implemented. AVAILABILITY AND IMPLEMENTATION: The web server is freely available at {http://reference-midori.info/server.php}. Oxford University Press 2018-11-01 2018-06-05 /pmc/articles/PMC6198853/ /pubmed/29878054 http://dx.doi.org/10.1093/bioinformatics/bty454 Text en © The Author(s) 2018. 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 | Applications Notes Leray, Matthieu Ho, Shian-Lei Lin, I-Jeng Machida, Ryuji J MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title | MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title_full | MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title_fullStr | MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title_full_unstemmed | MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title_short | MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
title_sort | midori server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198853/ https://www.ncbi.nlm.nih.gov/pubmed/29878054 http://dx.doi.org/10.1093/bioinformatics/bty454 |
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