Distribution-based clustering: Using ecology to refine the operational taxonomic unit

Applied and Environmental Microbiology

Volumn 79, Issue 21, 2013, Pages 6593-6603

  Preheim, Sarah P ^a   Perrott, Allison R ^a   Martin Platero, Antonio M ^a   Gupta, Anika ^a   Alm, Eric J ^a  

^a Massachusetts Institute of Technology Cambridge   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

16S RRNA SEQUENCES; 16S RRNA SEQUENCING; BACTERIAL POPULATION; ENVIRONMENTAL SAMPLE; HIGHLY-CORRELATED; MICROBIAL COMMUNITIES; OPERATIONAL TAXONOMIC UNITS; UNDERLYING DISTRIBUTION;

ERRORS; POPULATION STATISTICS; RNA;

POPULATION DISTRIBUTION;

ALGORITHM; CORRELATION; DATA ACQUISITION; ERROR ANALYSIS; GENETIC ANALYSIS; MICROBIAL COMMUNITY; POPULATION DISTRIBUTION; POPULATION GENETICS; POPULATION STRUCTURE; RNA; TAXONOMY;

PRIMER DNA; RNA 16S;

ALGORITHM; ARTICLE; BIOLOGY; CLASSIFICATION; CLUSTER ANALYSIS; DNA SEQUENCE; GENETICS; METHODOLOGY; MICROFLORA; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; REAL TIME POLYMERASE CHAIN REACTION; SENSITIVITY AND SPECIFICITY; SPECIES DIFFERENCE;

ALGORITHMS; BASE SEQUENCE; CLASSIFICATION; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DNA PRIMERS; MICROBIOTA; MOLECULAR SEQUENCE DATA; REAL-TIME POLYMERASE CHAIN REACTION; RNA, RIBOSOMAL, 16S; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS, DNA; SPECIES SPECIFICITY;

EID: 84886937146     PISSN: 00992240     EISSN: 10985336     Source Type: Journal    
DOI: 10.1128/AEM.00342-13     Document Type: Article

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