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dc.creatorDelamare-Deboutteville, J.en_US
dc.creatorBarnes, A.en_US
dc.date.accessioned2019-12-03T08:56:44Z
dc.date.available2019-12-03T08:56:44Z
dc.identifier.citationPenang, Malaysia: WorldFish. Poster.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12348/3826
dc.description.abstractAquaculture is the world’s fastest growing food sector increasingly and is recognized for its potential to alleviate poverty and hunger in small-scale systems. However, progress is limited by diseases and lack of knowledge and tools to identify fish pathogens, track their origin and manage their spread. Whole genome sequencing informs how pathogens change and move through environments, permitting implementation of evidence-based biosecurity to minimize disease impact. Offsite sequencing services are expensive and cause prohibitive delays. The project proposes leveraging offline supervised machine learning associated with the MinION portable sequencing device for low-cost diagnostics of fish pathogens in remote locations, allowing real-time disease investigation and data-driven management.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherWorldFish (WF)en_US
dc.rightsCC-BY-4.0en_US
dc.subjectlife below wateren_US
dc.subjectFishen_US
dc.titleRapid genomic detection of aquaculture pathogensen_US
dc.typePosteren_US
cg.contributor.crpFISHen_US
cg.contributor.funderCGIAR System Officeen_US
cg.coverage.regionGlobalen_US
cg.subject.agrovocaquacultureen_US
cg.subject.agrovocdiseasesen_US
cg.subject.agrovocfishen_US
cg.contributor.affiliationThe University of Queenslanden_US
cg.contributor.affiliationWorldFishen_US
cg.identifier.statusOpen accessen_US
cg.contribution.worldfishauthorDelamare-Deboutteville, J.en_US
cg.description.themeSustainable aquacultureen_US
cg.identifier.urlhttps://hdl.handle.net/20.500.12348/3826en_US
cg.creator.idJerome Delamare-Deboutteville: 0000-0003-4169-2456en_US


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