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      Responses of CH4 flux and microbial diversity to changes in rainfall amount and frequencies in a wet meadow in the Tibetan Plateau

      , , , , , ,
      CATENA
      Elsevier BV

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

          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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            UPARSE: highly accurate OTU sequences from microbial amplicon reads.

            Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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              An extraction method for measuring soil microbial biomass C

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                Author and article information

                Journal
                CATENA
                CATENA
                Elsevier BV
                03418162
                July 2021
                July 2021
                : 202
                : 105253
                Article
                10.1016/j.catena.2021.105253
                f782b86b-61e1-455f-a585-ff5b510d2962
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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