MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure
Kim J, Levy E, Ferbrache A, Stepanowsky P, Farcas C, Wang S, Brunner S, Bath T, Wu Y, Ohno-Machado L. MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure. Bioinformatics 2014, 30: 2826-2827. PMID: 24907367, PMCID: PMC4173015, DOI: 10.1093/bioinformatics/btu377.Peer-Reviewed Original ResearchConceptsWeb servicesWeb reportsLarge input filesNovel feature extractionEnd performance improvementsExploration of resultsGPU infrastructureInteractive visualizationJavaScript frameworkParallel computingGPU devicesHypertext PreprocessorCUDA CFeature extractionDrop operationInput filesPlot generationSalient featuresPerformance improvementInfrastructureNodesServicesData analysisComputingBrowserGAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda
Wang S, Kim J, Jiang X, Brunner S, Ohno-Machado L. GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda. BMC Medical Genomics 2014, 7: s9. PMID: 25077821, PMCID: PMC4101446, DOI: 10.1186/1755-8794-7-s1-s9.Peer-Reviewed Original ResearchConceptsCompute Unified Device ArchitectureGraphics processing unitsHigh performance computeParallel computingNVIDIA Compute Unified Device ArchitectureUnified Device ArchitectureMultiple test datasetsGiga cell updatesTimes performance gainsSmith-Waterman algorithmGPU developersSW implementationSource codeExecution timeGHz CPUIntel XeonLong reference sequencesProcessing unitTarget identification algorithmCell updatesTest datasetProjects/Such large scalePerformance gainsBiomedical research community