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SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB
Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool f...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2175337/ https://www.ncbi.nlm.nih.gov/pubmed/17947321 http://dx.doi.org/10.1093/nar/gkm864 |
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author | Pruesse, Elmar Quast, Christian Knittel, Katrin Fuchs, Bernhard M. Ludwig, Wolfgang Peplies, Jörg Glöckner, Frank Oliver |
author_facet | Pruesse, Elmar Quast, Christian Knittel, Katrin Fuchs, Bernhard M. Ludwig, Wolfgang Peplies, Jörg Glöckner, Frank Oliver |
author_sort | Pruesse, Elmar |
collection | PubMed |
description | Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. |
format | Text |
id | pubmed-2175337 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-21753372008-01-07 SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB Pruesse, Elmar Quast, Christian Knittel, Katrin Fuchs, Bernhard M. Ludwig, Wolfgang Peplies, Jörg Glöckner, Frank Oliver Nucleic Acids Res Computational Biology Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. Oxford University Press 2007-12 2007-10-18 /pmc/articles/PMC2175337/ /pubmed/17947321 http://dx.doi.org/10.1093/nar/gkm864 Text en © 2007 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Pruesse, Elmar Quast, Christian Knittel, Katrin Fuchs, Bernhard M. Ludwig, Wolfgang Peplies, Jörg Glöckner, Frank Oliver SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title_full | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title_fullStr | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title_full_unstemmed | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title_short | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB |
title_sort | silva: a comprehensive online resource for quality checked and aligned ribosomal rna sequence data compatible with arb |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2175337/ https://www.ncbi.nlm.nih.gov/pubmed/17947321 http://dx.doi.org/10.1093/nar/gkm864 |
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