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dc.contributor.authorChiu, Chih-Minen_US
dc.contributor.authorLin, Feng-Maoen_US
dc.contributor.authorChang, Tzu-Haoen_US
dc.contributor.authorHuang, Wei-Chihen_US
dc.contributor.authorLiang, Chaoen_US
dc.contributor.authorWu, Wei-Yunen_US
dc.contributor.authorYang, Tzu-Lingen_US
dc.contributor.authorWeng, Shun-Longen_US
dc.contributor.authorHuang, Hsien-Daen_US
dc.date.accessioned2014-12-08T15:30:53Z-
dc.date.available2014-12-08T15:30:53Z-
dc.date.issued2013en_US
dc.identifier.isbn978-84-15814-13-9en_US
dc.identifier.urihttp://hdl.handle.net/11536/22046-
dc.description.abstractThe human body plays host to a vast array of bacteria which are harmful or beneficial. Next generation sequencing technology have increased its accuracy in identifying bacteria. This work develops a novel platform for rapidly detecting probiotics and pathogens based on sequencing results of 16S rRNA. A database that recorded the species of probiotics and pathogens from literature was constructed, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. A bacteria disease risk model for seven diseases was constructed based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species for clinical microbiology applications. Detecting how probiotics and pathogens inhabit humans and affect their health significantly contributes to develop a diagnosis and treatment method.en_US
dc.language.isoen_USen_US
dc.titleClinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencingen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS IWBBIO 2013: INTERNATIONAL WORK-CONFERENCE ON BIOINFORMATION AND BIOMEDICAL ENGINEERINGen_US
dc.citation.spage29en_US
dc.citation.epage40en_US
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000322416100005-
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