DICP OpenIR
Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis
Wen, Jie2; Zhang, Xiaohui2; Gao, Peng1; Jiang, Qiuhong2
Keyword16s Rrna Gene 16s-23s Rrna Spacer Region Gene Capillary Electrophoresis Artificial Neural Network (Ann) Single-strand Conformation Polymorphism (Sscp) Restriction Fragment Length Polymorphism (Rflp)
Source PublicationJOURNAL OF CLINICAL LABORATORY ANALYSIS
2008
DOI10.1002/jcla.20224
Volume22Issue:1Pages:14-20
Indexed BySCI
SubtypeArticle
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS SubjectMedical Laboratory Technology
WOS Research AreaMedical Laboratory Technology
WOS Keyword16S RIBOSOMAL-RNA ; STRAND CONFORMATION POLYMORPHISM ; RAPID IDENTIFICATION ; SEQUENCE-ANALYSIS ; ELECTROPHORESIS ; GENE ; POLYACRYLAMIDE ; MICROARRAY ; PATHOGENS ; REGION
AbstractThe 16S ribosomal ribonucleic acid (rRNA) and 16S-23S rRNA spacer region genes are commonly used as taxonomic and phylogenetic tools. In this study, two pairs of fluorescent-labeled primers for 16S rRNA genes and one pair of primers for 16S-23S rRNA spacer region genes were selected to amplify target sequences of 317 isolates from positive blood cultures. The polymerase chain reaction (PCR) products of both were then subjected to restriction fragment length polymorphism (RFLP) analysis by capillary electrophoresis after incomplete digestion by Hae III. For products of 16S rRNA genes, single-strand conformation polymorphism (SSCP) analysis was also performed directly. When the data were processed by artificial neural network (ANN), the accuracy of prediction based on 16S-23S rRNA spacer region gene RFLP data was much higher than that of prediction based on 16S rRNA gene SSCP analysis data(98.0% vs. 79.6%). This study proved that the utilization of ANN as a pattern recognition method was a valuable strategy to simplify bacterial identification when relatively complex data were encountered.
Language英语
WOS IDWOS:000253587800003
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/140790
Collection中国科学院大连化学物理研究所
Affiliation1.Chinese Acad Sci, Dalian Inst Chem Phys, Natl Chromatog R&A Ctr, Dalian 116023, Peoples R China
2.Dalian Municipal Cent Hosp, Dalian, Peoples R China
Recommended Citation
GB/T 7714
Wen, Jie,Zhang, Xiaohui,Gao, Peng,et al. Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis[J]. JOURNAL OF CLINICAL LABORATORY ANALYSIS,2008,22(1):14-20.
APA Wen, Jie,Zhang, Xiaohui,Gao, Peng,&Jiang, Qiuhong.(2008).Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis.JOURNAL OF CLINICAL LABORATORY ANALYSIS,22(1),14-20.
MLA Wen, Jie,et al."Comparison between two PCR-based bacterial identification methods through artificial neural network data analysis".JOURNAL OF CLINICAL LABORATORY ANALYSIS 22.1(2008):14-20.
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