About: Optimization and clinical validation of a pathogen detection microarray

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Optimization and clinical validation of a pathogen detection microarray
Creator	Kartasasmita, Cissy Sung, Wing-Kin Hibberd, Martin Af, Eric Heng, Wah Lee, Charlie Leong, Wan Miller, Lance Shirlena, W Soh, Wong, Christopher Yee,
Source	Medline; PMC
abstract	DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics.
has issue date	2007-05-28(xsd:dateTime)
bibo:doi	10.1186/gb-2007-8-5-r93
bibo:pmid	17531104
has license	cc-by
sha1sum (hex)	40e94ea7aba6cfaed881217032da16d4a5c2fd1d
schema:url	https://doi.org/10.1186/gb-2007-8-5-r93
resource representing a document's title	Optimization and clinical validation of a pathogen detection microarray
has PubMed Central identifier	PMC1929155
has PubMed identifier	17531104
schema:publication	Genome Biol
resource representing a document's body	covid:40e94ea7aba6cfaed881217032da16d4a5c2fd1d#body_text
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is part of of	Optimization and clinical validation of a pathogen detection microarray DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics. covid:40e94ea7aba6cfaed881217032da16d4a5c2fd1d#body_text

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