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The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

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      Abstract

      SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.

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      Affiliations
      1Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, 2Jacobs University Bremen gGmbH, School of Engineering and Science, D-28759 Bremen and 3Ribocon GmbH, D-28359 Bremen, Germany
      Author notes
      *To whom correspondence should be addressed. Tel: +49 421 2028970; Fax: +49 421 2028580; Email: fog@ 123456mpi-bremen.de

      The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

      Journal
      Nucleic Acids Res
      Nucleic Acids Res
      nar
      nar
      Nucleic Acids Research
      Oxford University Press
      0305-1048
      1362-4962
      January 2013
      27 November 2012
      27 November 2012
      : 41
      : Database issue , Database issue
      : D590-D596
      23193283 3531112 10.1093/nar/gks1219 gks1219
      © The Author(s) 2012. Published by Oxford University Press.

      This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.

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      Pages: 7
      Categories
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      Genetics

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