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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dirros.openscience.si/IzpisGradiva.php?id=23689"><dc:title>Digital PCR-based genotyping: a precision approach to HCMV drug resistance</dc:title><dc:creator>Milavec,	Mojca	(Avtor)
	</dc:creator><dc:creator>Cvelbar,	Tašja	(Avtor)
	</dc:creator><dc:creator>Bogožalec Košir,	Alexandra	(Avtor)
	</dc:creator><dc:subject>digital PCR</dc:subject><dc:subject>human cytomegalovirus</dc:subject><dc:subject>antimicrobial drug resistance</dc:subject><dc:subject>mutations</dc:subject><dc:description>The genotyping workflow described uses digital PCR (dPCR) to detect and quantify drug resistance mutations in human cytomegalovirus (HCMV). The method focuses on the detection and quantification of three common mutations in the UL97 gene at codons 460, 594, and 595, which are responsible for the majority of ganciclovir-resistant clinical isolates. The dPCR approach offers high sensitivity and accuracy, making it suitable for routine testing as well as a reference measurement procedure for external quality assessment schemes. The workflow includes several key steps: DNA isolation, preparation of the dPCR reaction mixture, partitioning, thermocycling, and data analysis. This method improves the detection capabilities of HCMV drug resistance and provides a robust and efficient tool for clinical and research applications.</dc:description><dc:date>2025</dc:date><dc:date>2025-09-25 10:16:15</dc:date><dc:type>Neznano</dc:type><dc:identifier>23689</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
