Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis

Journal of Clinical Laboratory Analysis

Volumn 22, Issue 1, 2008, Pages 14-20

  Wen, Jie ^a   Zhang, Xiaohui ^a   Gao, Peng ^b   Jiang, Qiuhong ^a  

^a DALIAN MUNICIPAL CENTRAL HOSPITAL   (China)

^b DALIAN INSTITUTE OF CHEMICAL PHYSICS   (China)

Author keywords

16S rRNA gene; 16S 23S rRNA spacer region gene; Artificial neural network (ANN); Capillary electrophoresis; Restriction fragment length polymorphism (RFLP); Single strand conformation polymorphism (SSCP)

Indexed keywords

FLUORESCENT DYE; RNA 16S; RNA 23S;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACTERIUM IDENTIFICATION; BLOOD CULTURE; CAPILLARY ELECTROPHORESIS; CONTROLLED STUDY; DATA ANALYSIS; GENE AMPLIFICATION; GENE SEQUENCE; INTERMETHOD COMPARISON; MOLECULAR RECOGNITION; NONHUMAN; PATTERN RECOGNITION; PHYLOGENY; POLYMERASE CHAIN REACTION; PREDICTION; RESTRICTION FRAGMENT LENGTH POLYMORPHISM; RNA GENE; SINGLE STRAND CONFORMATION POLYMORPHISM;

BACTERIA; BACTERIAL TYPING TECHNIQUES; DNA, BACTERIAL; ELECTROPHORESIS, AGAR GEL; ELECTROPHORESIS, CAPILLARY; HUMANS; NEURAL NETWORKS (COMPUTER); POLYMERASE CHAIN REACTION; POLYMORPHISM, RESTRICTION FRAGMENT LENGTH; POLYMORPHISM, SINGLE-STRANDED CONFORMATIONAL; RNA, RIBOSOMAL, 16S; RNA, RIBOSOMAL, 23S;

BACTERIA (MICROORGANISMS);

EID: 39449134506     PISSN: 08878013     EISSN: 10982825     Source Type: Journal    
DOI: 10.1002/jcla.20224     Document Type: Article

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