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• W2052961519 abstract "Deep sequencing of the 16S rRNA gene provides a comprehensive view of bacterial communities in a particular environment and has expanded our ability to study the impact of the microflora on human health and disease. Current analysis methods rely on comparisons of the sequences generated with an expanding but limited set of annotated 16S rRNA sequences or phylogenic clustering of sequences based on arbitrary similarity cutoffs. We describe a novel approach to characterize bacterial composition using deep sequencing of 16S rRNA gene. Our method defines operational taxonomic units based on phylogenetic tree reconstruction and dynamic clustering of sequences using solely sequencing data. These OTUs can be used to identify differences in bacteria abundance between environments. This approach can perform better than previous phylogenetic methods and will significantly improve our understanding of the microfloral role on human diseases by providing a comprehensive analysis of the microbial composition from various bacterial communities." @default.
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• W2052961519 date "2011-10-01" @default.
• W2052961519 modified "2023-09-23" @default.
• W2052961519 title "A novel method for determining microflora composition using dynamic phylogenetic analysis of 16S ribosomal RNA deep sequencing data" @default.
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• W2052961519 doi "https://doi.org/10.1016/j.ygeno.2011.04.002" @default.
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