2023
Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions
Kuo T, Pham A, Edelson M, Kim J, Chan J, Gupta Y, Ohno-Machado L, Anderson D, Balacha C, Bath T, Baxter S, Becker-Pennrich A, Bell D, Bernstam E, Ngan C, Day M, Doctor J, DuVall S, El-Kareh R, Florian R, Follett R, Geisler B, Ghigi A, Gottlieb A, Hinske L, Hu Z, Ir D, Jiang X, Kim K, Kim J, Knight T, Koola J, Kuo T, Lee N, Mansmann U, Matheny M, Meeker D, Mou Z, Neumann L, Nguyen N, Nick A, Ohno-Machado L, Park E, Paul P, Pletcher M, Post K, Rieder C, Scherer C, Schilling L, Soares A, SooHoo S, Soysal E, Steven C, Tep B, Toy B, Wang B, Wu Z, Xu H, Yong C, Zheng K, Zhou Y, Zucker R. Blockchain-enabled immutable, distributed, and highly available clinical research activity logging system for federated COVID-19 data analysis from multiple institutions. Journal Of The American Medical Informatics Association 2023, 30: 1167-1178. PMID: 36916740, PMCID: PMC10198529, DOI: 10.1093/jamia/ocad049.Peer-Reviewed Original ResearchConceptsFederated data analysisUser activity logsSmart contract deploymentRun-time efficiencyData analysis systemData analysis activitiesActivity logsData discoveryQuerying timeBlockchain systemBlockchain technologyNetwork transactionsCOVID-19 data analysisMultiple institutionsLow deploymentBlockchainGitHub repositoryMultiple nodesLarge networksQueriesAnalysis activitiesHigh availabilityLanguage codeBaseline solutionData analysis
2022
The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition
Kuo T, Jiang X, Tang H, Wang X, Harmanci A, Kim M, Post K, Bu D, Bath T, Kim J, Liu W, Chen H, Ohno-Machado L. The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition. Journal Of The American Medical Informatics Association 2022, 29: 2182-2190. PMID: 36164820, PMCID: PMC9667175, DOI: 10.1093/jamia/ocac165.Peer-Reviewed Original ResearchConceptsSensitive personal informationGenomic data analysisPotential future research directionsPersonal informationSecurity concernsGenomics data repositoryData repositoryReport lessonsProtection techniquesFuture research directionsPrivacyResearch directionsData usePractical challengesGenomic dataData analysisAnonymizationCommunity effortsRepositorySecurityBiomedical researchInformationDataChallenges
2014
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 analysisComputingBrowser