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 ResearchMeSH KeywordsComputational BiologyComputer GraphicsInternetMicroRNAsProgramming LanguagesSequence Analysis, RNASoftwareConceptsWeb 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