Self-organizing maps: A tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence

Journal of Biosciences

Volumn 35, Issue 4, 2010, Pages 617-627

  Raje, D V ^a   Purohit, H J ^a   Badhe, Y P ^b   Tambe, S S ^b   Kulkarni, B D ^b  

^a NATIONAL ENVIRONMENTAL ENGINEERING RESEARCH INSTITUTE   (India)

^b NATIONAL CHEMICAL LABORATORY   (India)

Author keywords

Curvilinear component analysis; principal component analysis; self organizing maps

Indexed keywords

DNA 16S; TETRAMER;

ARTIFICIAL NEURAL NETWORK; DNA; MAP; PRINCIPAL COMPONENT ANALYSIS; RNA; SELF ORGANIZATION; TAXONOMY;

ACIDIPHILIUM; ALPHAPROTEOBACTERIA; ARTICLE; ARTIFICIAL NEURAL NETWORK; BETAPROTEOBACTERIA; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; DNA DETERMINATION; DNA SEQUENCE; NONHUMAN; NUCLEOTIDE SEQUENCE; PARACOCCUS; PRINCIPAL COMPONENT ANALYSIS; PROTEIN LOCALIZATION; SEQUENCE ALIGNMENT; TAXONOMY; THIOBACILLUS;

ALGORITHMS; BASE SEQUENCE; COMPUTER SIMULATION; GRAM-NEGATIVE BACTERIA; GRAM-POSITIVE BACTERIA; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDES; PHYLOGENY; PRINCIPAL COMPONENT ANALYSIS; RNA, BACTERIAL; RNA, RIBOSOMAL, 16S;

ACIDIPHILIUM; STARKEYA; TETRA; THIOBACILLUS;

EID: 78651334076     PISSN: 02505991     EISSN: 02505991     Source Type: Journal    
DOI: 10.1007/s12038-010-0070-y     Document Type: Article

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