2020
Impact of Diverse Data Sources on Computational Phenotyping
Wang L, Olson J, Bielinski S, St. Sauver J, Fu S, He H, Cicek M, Hathcock M, Cerhan J, Liu H. Impact of Diverse Data Sources on Computational Phenotyping. Frontiers In Genetics 2020, 11: 556. PMID: 32582289, PMCID: PMC7283539, DOI: 10.3389/fgene.2020.00556.Peer-Reviewed Original ResearchDiverse data sourcesElectronic health recordsComputational phenotypingData fragmentationPhenotyping algorithmData sourcesRochester Epidemiology ProjectPositive predictive valueSingle data sourceFalse negative rateRheumatoid arthritisEHR dataMultiple health care systemsHealth recordsMayo dataIncomplete dataType 2 diabetes mellitusAlgorithmPhenotype informationIntegrated sourceHealth care systemScientific discoveryT2DM controlDiabetes mellitusMedical recordsStatistical Methods in Genome-Wide Association Studies
Sun N, Zhao H. Statistical Methods in Genome-Wide Association Studies. Annual Review Of Biomedical Data Science 2020, 3: 1-24. DOI: 10.1146/annurev-biodatasci-030320-041026.Peer-Reviewed Original ResearchGenome-wide association studiesAssociation studiesTraits of interestGenetic architectureIdentification of variantsGWAS dataStatistical methodologyStatistical challengesGenetic risk prediction modelsGenetic markersStatistical methodsHuman diseasesPhenotype informationGenetic variantsTraitsGenotype informationScientific goalsRecent progressGenesVariantsTens of thousandsHundreds of thousandsPrediction modelPathwayThousands
2016
Genome 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
2014
PhenDisco: phenotype discovery system for the database of genotypes and phenotypes
Doan S, Lin K, Conway M, Ohno-Machado L, Hsieh A, Feupe S, Garland A, Ross M, Jiang X, Farzaneh S, Walker R, Alipanah N, Zhang J, Xu H, Kim H. PhenDisco: phenotype discovery system for the database of genotypes and phenotypes. Journal Of The American Medical Informatics Association 2014, 21: 31-36. PMID: 23989082, PMCID: PMC3912702, DOI: 10.1136/amiajnl-2013-001882.Peer-Reviewed Original ResearchConceptsNew information retrieval systemInformation retrieval systemsInformation retrieval toolsDatabase of GenotypesText processing toolsRetrieval systemSearch scenariosDiscovery systemRetrieval toolsAuthorized usersNon-standardized wayCross-study validationSearch comparisonProcessing toolsPromising performanceUsersPhenotype informationDatabaseInformationBiotechnology InformationQueriesMetadataEntrezResourcesSystem
2012
Thousands of missed genes found in bacterial genomes and their analysis with COMBREX
Wood DE, Lin H, Levy-Moonshine A, Swaminathan R, Chang YC, Anton BP, Osmani L, Steffen M, Kasif S, Salzberg SL. Thousands of missed genes found in bacterial genomes and their analysis with COMBREX. Biology Direct 2012, 7: 37. PMID: 23111013, PMCID: PMC3534567, DOI: 10.1186/1745-6150-7-37.Peer-Reviewed Original ResearchConceptsProtein-coding genesProkaryotic genome annotationCost of sequencingGenome annotationHypothetical proteinsBacterial genomesProkaryotic genomesShort genesArcady MushegianLikely geneGenesPhenotype informationGenomeHomologPotential targetPathogenic organismsAnnotationSequencingProteinFunction databaseAnnotation methodDramatic reductionGenBankOrganismsPharmaceutical research
2007
A population-based study in Ghana to investigate inter-individual variation in plasma t-PA and PAI-1.
Williams SM, Stocki S, Jiang L, Brew K, Gordon S, Vaughan DE, Brown NJ, Poku KA, Moore JH. A population-based study in Ghana to investigate inter-individual variation in plasma t-PA and PAI-1. Ethnicity & Disease 2007, 17: 492-7. PMID: 17985503.Peer-Reviewed Original ResearchConceptsPlasminogen activator inhibitor-1Tissue-type plasminogen activatorInter-individual variationGenetic architectureSignificant genetic componentGenetic analysisGenetic componentPhenotype informationPopulation-based studyPlasma t-PAActivator inhibitor-1Inhibitor-1Unrelated subjectsLarge-scale population-based studyStudy designChronic disease statusSystolic blood pressurePlasminogen activatorRisk of thrombosisProtein
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