2023
Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program
Wang X, Ryu J, Kim J, Ramirez A, Mayo K, Condon H, Vaitinadin N, Ohno-Machado L, Talavera G, Ellinor P, Lubitz S, Choi S. Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program. Journal Of Human Genetics 2023, 68: 565-570. PMID: 37072623, PMCID: PMC10524735, DOI: 10.1038/s10038-023-01147-z.Peer-Reviewed Original ResearchConceptsDiverse human populationsGenomic dataGene-based burden testsWhole genome sequencesRare variant analysisHuman populationQuantitative traitsBurden testsRare lossLociComplex diseasesGenetic associationVariant analysisFunction variantsCardiometabolic traitsRare variantsTraitsBiomedical researchGIGYF1VariantsNPR2ACANSequencePopulationLDLR
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
2020
EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning
Kuo T, Gabriel R, Cidambi K, Ohno-Machado L. EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning. Journal Of The American Medical Informatics Association 2020, 27: 747-756. PMID: 32364235, PMCID: PMC7309256, DOI: 10.1093/jamia/ocaa023.Peer-Reviewed Original ResearchConceptsBlockchain technologyCentral serverServer-based methodBenefits of blockchainData protection policiesCentralized serverArtificial intelligenceModel learningDecentralized approachSmall datasetsBlockchainServerComputation strategySingle pointGeneralizable modelCost of efficiencyGenomic datasetsDatasetDistributed modelTechnologyGenomic dataMultiple institutionsDiscrimination powerIntelligencePotential advantages/disadvantages
2017
Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks
Raisaro J, Tramèr F, Ji Z, Bu D, Zhao Y, Carey K, Lloyd D, Sofia H, Baker D, Flicek P, Shringarpure S, Bustamante C, Wang S, Jiang X, Ohno-Machado L, Tang H, Wang X, Hubaux J. Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks. Journal Of The American Medical Informatics Association 2017, 24: 799-805. PMID: 28339683, PMCID: PMC5881894, DOI: 10.1093/jamia/ocw167.Peer-Reviewed Original Research
2016
Protecting genomic data analytics in the cloud: state of the art and opportunities
Tang H, Jiang X, Wang X, Wang S, Sofia H, Fox D, Lauter K, Malin B, Telenti A, Xiong L, Ohno-Machado L. Protecting genomic data analytics in the cloud: state of the art and opportunities. BMC Medical Genomics 2016, 9: 63. PMID: 27733153, PMCID: PMC5062944, DOI: 10.1186/s12920-016-0224-3.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsHuman genomic dataSecure computation techniquesPublic cloud environmentSecure computation methodsGenomic data analyticsReal-world environmentsSecond Critical AssessmentSecure outsourcingCloud environmentCryptographic technologyPublic cloudSecure collaborationUnauthorized usersComputation tasksData privacyData analyticsBiomedical computingData scientistsComputational environmentGenomic dataWorld environmentComputation techniquesMultiple organizationsPractical algorithmPrivacyGenome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States
Wang S, Jiang X, Singh S, Marmor R, Bonomi L, Fox D, Dow M, Ohno‐Machado L. Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States. Annals Of The New York Academy Of Sciences 2016, 1387: 73-83. PMID: 27681358, PMCID: PMC5266631, DOI: 10.1111/nyas.13259.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsData privacySensitive individual informationComputer science communityReal-world problemsUnauthorized partiesHuman genomic dataPrivacy breachesData accessData sharingData accessibilityConfidentiality protectionGenomic dataSpectrum of techniquesIndividual informationPrivacyScience communityPhenotype informationTechnical approachPotential solutionsCurrent common practiceBiomedical researchResearch purposesConfidentialityInformationSharing
2015
Preserving Genome Privacy in Research Studies
Wang S, Jiang X, Fox D, Ohno-Machado L. Preserving Genome Privacy in Research Studies. 2015, 425-441. DOI: 10.1007/978-3-319-23633-9_16.Peer-Reviewed Original ResearchGenome privacyPrivacy researchBetter privacy protectionObfuscation of dataSecure data repositoryLoss of privacyData use agreementsPrivacy challengesPrivacy problemsPrivacy protectionAttack modelIndividual privacyData sharingMassive collectionPrivacyData repositoryTraditional clinical informationScientific discoveryGenomic dataData analysis methodsBig challengeUse agreementsBiomedical communityTechnical aspects
2014
A community assessment of privacy preserving techniques for human genomes
Jiang X, Zhao Y, Wang X, Malin B, Wang S, Ohno-Machado L, Tang H. A community assessment of privacy preserving techniques for human genomes. BMC Medical Informatics And Decision Making 2014, 14: s1. PMID: 25521230, PMCID: PMC4290799, DOI: 10.1186/1472-6947-14-s1-s1.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsBiomedical dataPrivacy preserving techniquesPrivacy protection techniquesData privacyBiomedical computingHuman genomic dataData donorsDissemination techniquesPersonal Genome ProjectRaw dataProtection techniquesRigorous protectionPrivacyGenomic dataFinal resultsComputingCommunity effortsAnalysis outcomesChallengesTechniqueDataProjectChoosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery
Zhao Y, Wang X, Jiang X, Ohno-Machado L, Tang H. Choosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery. Journal Of The American Medical Informatics Association 2014, 22: 100-108. PMID: 25352565, PMCID: PMC4433380, DOI: 10.1136/amiajnl-2014-003043.Peer-Reviewed Original ResearchConceptsData ownersData usersHuman genomic datasetsHuman genomic dataPatient privacyPrivacyGeneration approachUsersData selectionReal dataDatasetGenomic datasetsPrivate solicitationDNA datasetsScientific discoveryNew approachGenomic dataHigh confidencePilot versionEvaluation methodRight choiceOwnersAlgorithmNew techniqueDisease marker discovery
2012
Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
Wu Y, Jiang X, Kim J, Ohno-Machado L. Grid Binary LOgistic REgression (GLORE): building shared models without sharing data. Journal Of The American Medical Informatics Association 2012, 19: 758-764. PMID: 22511014, PMCID: PMC3422844, DOI: 10.1136/amiajnl-2012-000862.Peer-Reviewed Original ResearchConceptsIntegrity of communicationCentralized data sourcesTraditional LR modelCentral repositoryComputational costData sourcesData setsSame formatPatient dataComputationGenomic dataRare patternRelevant dataLR modelPrediction valueSetRepositoryPartial elementsFormatClassificationCommunicationModelDataPatient setPerform
2010
TGF-beta1 interactome: metastasis and beyond.
Perera M, Tsang C, Distel R, Lacy J, Ohno-Machado L, Ricchiuti V, Samaranayake L, Smejkal G, Smith M, Trachtenberg A, Kuo W. TGF-beta1 interactome: metastasis and beyond. Cancer Genomics & Proteomics 2010, 7: 217-29. PMID: 20656987.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsDifferential expression profilesCancer therapeuticsPersonalized cancer therapeuticsRegulation of tumorEffective cancer therapeuticsNovel cancer biomarkersGenomic dataExpression profilesMetastatic attributesInteractomeUbiquitous cytokineTumor progressionCancer biomarkersPolarity changeTherapeuticsValuable insightsImmense valueRegulationInsightsInducerImportant stepMappingGrowth