2022
An Artificial Intelligence-guided signature reveals the shared host immune response in MIS-C and Kawasaki disease
Ghosh P, Katkar G, Shimizu C, Kim J, Khandelwal S, Tremoulet A, Kanegaye J, Bocchini J, Das S, Burns J, Sahoo D. An Artificial Intelligence-guided signature reveals the shared host immune response in MIS-C and Kawasaki disease. Nature Communications 2022, 13: 2687. PMID: 35577777, PMCID: PMC9110726, DOI: 10.1038/s41467-022-30357-w.Peer-Reviewed Original ResearchConceptsKawasaki diseaseHost immune responseLaboratory parametersImmune responseSARS-CoV-2 infectionInflammatory syndromeCytokine stormSerum cytokinesClinical featuresCytokine pathwaysCardiac phenotypeSyndromeGene signaturePediatric syndromesViral pandemicHeart tissueCOVID-19COVID-19 pandemicProximal pathwayDiseaseSeverityImmunopathogenesisPandemicCytokinesIllness
2021
Kawasaki Disease Patient Stratification and Pathway Analysis Based on Host Transcriptomic and Proteomic Profiles
Jackson H, Menikou S, Hamilton S, McArdle A, Shimizu C, Galassini R, Huang H, Kim J, Tremoulet A, Thorne A, Fischer R, de Jonge M, Kuijpers T, Wright V, Burns J, Casals-Pascual C, Herberg J, Levin M, Kaforou M, On Behalf Of The Perform Consortium. Kawasaki Disease Patient Stratification and Pathway Analysis Based on Host Transcriptomic and Proteomic Profiles. International Journal Of Molecular Sciences 2021, 22: 5655. PMID: 34073389, PMCID: PMC8198135, DOI: 10.3390/ijms22115655.Peer-Reviewed Original ResearchConceptsKawasaki diseaseViral infectionHost responseKD patientsAcute inflammatory disordersAnti-bacterial responsePathway analysisBacterial patientsInflammatory disordersInflammatory responsePatient stratificationCommon triggerPatientsKD samplesHost transcriptomicsInfectionProteomic profilesOmics profilesDifferent triggersDiagnostic signatureResponseInflammationTriggersLevelsEtiology
2017
PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens
Spahn P, Bath T, Weiss R, Kim J, Esko J, Lewis N, Harismendy O. PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens. Scientific Reports 2017, 7: 15854. PMID: 29158538, PMCID: PMC5696473, DOI: 10.1038/s41598-017-16193-9.Peer-Reviewed Original ResearchConceptsCRISPR/Large-scale genetic screensCRISPR/Cas9Publication-ready plotsSequence quality controlPlatform-independent analysisUser-friendly implementationLarge sequencing datasetsGenetic screenAnalysis optionsFunctional genomicsPooled screensSgRNA libraryBioinformatics toolsSequencing datasetsComprehensive functionalityExperimental biologistsBioinformatics expertiseArt toolsCustom libraryLimited functionalityTest datasetSequence extractionGene rankingIncreased popularity
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 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
2010
DSGeo: Software tools for cross-platform analysis of gene expression data in GEO
Lacson R, Pitzer E, Kim J, Galante P, Hinske C, Ohno-Machado L. DSGeo: Software tools for cross-platform analysis of gene expression data in GEO. Journal Of Biomedical Informatics 2010, 43: 709-715. PMID: 20435161, PMCID: PMC2934864, DOI: 10.1016/j.jbi.2010.04.007.Peer-Reviewed Original ResearchConceptsAggregation of dataData loaderRelational databaseGene expression dataUser preferencesData browserData browsingCross-platform dataSoftware toolsSeamless integrationCross-platform analysisGroups of dataQueriesExpression dataPublic gene expression dataSpecific sample characteristicsLarge resourcesBrowserToolBrowsingAnnotatingUsersRetrievalApplicationsPlatform
2009
Towards large-scale sample annotation in gene expression repositories
Pitzer E, Lacson R, Hinske C, Kim J, Galante P, Ohno-Machado L. Towards large-scale sample annotation in gene expression repositories. BMC Bioinformatics 2009, 10: s9. PMID: 19761579, PMCID: PMC2745696, DOI: 10.1186/1471-2105-10-s9-s9.Peer-Reviewed Original Research