2024
Leveraging Functional Annotations Improves Cross-Population Genetic Risk Prediction
Ye Y, Xu L, Zhao H. Leveraging Functional Annotations Improves Cross-Population Genetic Risk Prediction. ICSA Book Series In Statistics 2024, 453-471. DOI: 10.1007/978-3-031-50690-1_18.Peer-Reviewed Original ResearchPolygenic risk scoresFunctional annotationGenetic risk predictionStandard PRSPost-GWAS analysisPolygenic risk score modelCross-population predictionNon-European populationsGenetic resultsGenetic studiesRisk predictionCross populationsAnnoPredPRS methodsUK BiobankAnnotationRisk scoreTraits/diseasesLDpredPopulationP+TPoor transferBiobankBayesian frameworkBayesian network-based Mendelian randomization for variant prioritization and phenotypic causal inference
Sun J, Zhou J, Gong Y, Pang C, Ma Y, Zhao J, Yu Z, Zhang Y. Bayesian network-based Mendelian randomization for variant prioritization and phenotypic causal inference. Human Genetics 2024, 143: 1081-1094. PMID: 38381161, DOI: 10.1007/s00439-024-02640-x.Peer-Reviewed Original ResearchMendelian randomizationGenetic instrumental variablesGenomic dataIndividual-level dataInstrumental variablesUK BiobankFalse-positive discoveriesGenetic structureVariant prioritizationEffect estimatesMR methodsGene interactionsGenetic variantsCausal inferencePsychiatric disordersStatistical powerBlood pressureBayesian frameworkInference frameworkInferenceBiobankEstimationCausal relationshipsPleiotropyGenes
2023
A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy
Deng W, Li B, Wang J, Jiang W, Yan X, Li N, Vukmirovic M, Kaminski N, Wang J, Zhao H. A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy. Briefings In Bioinformatics 2023, 24: bbac616. PMID: 36631398, PMCID: PMC9851324, DOI: 10.1093/bib/bbac616.Peer-Reviewed Original Research
2022
A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth
Comess S, Chang HH, Warren JL. A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth. Biostatistics 2022, 25: 20-39. PMID: 35984351, PMCID: PMC10724312, DOI: 10.1093/biostatistics/kxac034.Peer-Reviewed Original ResearchConceptsFull conditional distributionsEfficient model fittingStatistical modeling approachDensity estimation approachBayesian settingKernel density estimation approachPosterior outputBayesian frameworkConditional distributionModel fittingEstimation approachAccurate inferenceKDE approachModeling approachComparison metricsExposure uncertaintyUncertaintySecond stageApproachFittingInferencePredictionSimulationsModel comparison metricsFirst stage
2021
Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling
Zhuang J, Dvornek N, Tatikonda S, Papademetris X, Ventola P, Duncan J. Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling. Lecture Notes In Computer Science 2021, 12729: 58-70. DOI: 10.1007/978-3-030-78191-0_5.Peer-Reviewed Original ResearchOrdinary differential equationsAdjoint methodNoisy observationsMultiple shooting methodNon-linear systemsLarge scale continuous systemsLarge-scale systemsParameter value estimationDifferential equationsAccurate gradient estimationExpectation-maximization algorithmNon-linear modelParameter estimationBayesian frameworkGradient estimationContinuous systemToy exampleLarge systemsReal fMRI dataEstimationValue estimationAlgorithmGood accuracyCausal modelingModel changesA fast likelihood approach for estimation of large phylogenies from continuous trait data
Peng J, Rajeevan H, Kubatko L, RoyChoudhury A. A fast likelihood approach for estimation of large phylogenies from continuous trait data. Molecular Phylogenetics And Evolution 2021, 161: 107142. PMID: 33713799, DOI: 10.1016/j.ympev.2021.107142.Peer-Reviewed Original ResearchConceptsContinuous trait dataMaximum likelihood estimatorMaximum likelihood estimatesMathematical propertiesHundreds of taxaInternal branch lengthsFast approximationAddition of taxaLarge-scale genomic dataCollection of methodsBayesian frameworkLikelihood estimatorLikelihood estimatesLikelihood approachMaximum likelihoodIntensive calculationsModel-based methodApproximationLarge phylogeniesComparable accuracyPossible phylogenyInferenceBranch lengthsEstimatorSuch data
2019
Joint Models for Time-to-Event Data and Longitudinal Biomarkers of High Dimension
Liu M, Sun J, Herazo-Maya JD, Kaminski N, Zhao H. Joint Models for Time-to-Event Data and Longitudinal Biomarkers of High Dimension. Statistics In Biosciences 2019, 11: 614-629. PMID: 33281995, PMCID: PMC7717673, DOI: 10.1007/s12561-019-09256-0.Peer-Reviewed Original ResearchCritical window variable selection: estimating the impact of air pollution on very preterm birth
Warren JL, Kong W, Luben TJ, Chang HH. Critical window variable selection: estimating the impact of air pollution on very preterm birth. Biostatistics 2019, 21: 790-806. PMID: 30958877, PMCID: PMC7422642, DOI: 10.1093/biostatistics/kxz006.Peer-Reviewed Original ResearchConceptsHierarchical Bayesian frameworkBayesian frameworkStatistical modelVariable selectionImproved estimationCritical windowPreterm birthRisk parametersVery preterm birthAdverse birth outcomesControl analysisExposure-disease relationshipsDifferent reproductive outcomesBirth outcomesPregnant womenReproductive outcomesCase/control analysis
2017
Leveraging functional annotations in genetic risk prediction for human complex diseases
Hu Y, Lu Q, Powles R, Yao X, Yang C, Fang F, Xu X, Zhao H. Leveraging functional annotations in genetic risk prediction for human complex diseases. PLOS Computational Biology 2017, 13: e1005589. PMID: 28594818, PMCID: PMC5481142, DOI: 10.1371/journal.pcbi.1005589.Peer-Reviewed Original ResearchMeSH KeywordsChromosome MappingData Interpretation, StatisticalData MiningDatabases, GeneticEpigenomicsGenetic Association StudiesGenetic Predisposition to DiseaseGenetic VariationGenome, HumanHumansLinkage DisequilibriumPolymorphism, Single NucleotideProportional Hazards ModelsQuantitative Trait LociRisk AssessmentConceptsGenome-wide association studiesFunctional annotationGenetic risk predictionDisease-associated genetic variantsLinkage disequilibriumIdentification of thousandsWide association studyHuman complex diseasesComplex diseasesGWAS summary statisticsHuman genetics researchAssociation studiesAnnoPredGenotype dataGenetic researchGenetic variantsRelevant variantsAnnotationDisequilibriumMost diseasesDiverse typesSummary statisticsVariantsBayesian frameworkPrecision medicine
2013
Bayesian Analysis of Time-Series Data under Case-Crossover Designs: Posterior Equivalence and Inference
Li S, Mukherjee B, Batterman S, Ghosh M. Bayesian Analysis of Time-Series Data under Case-Crossover Designs: Posterior Equivalence and Inference. Biometrics 2013, 69: 925-936. PMID: 24289144, PMCID: PMC4108592, DOI: 10.1111/biom.12102.Peer-Reviewed Original ResearchConceptsSemi-parametric Bayesian approachLikelihood-based approachRandom nuisance parametersTime series analysisFrequentist literatureNuisance parametersDirichlet processInferential issuesConditional likelihoodPosterior distributionRisk functionTime seriesBayesian workFrequentist approachCase-crossover designSimulation studyRestrictive assumptionsBayesian approachTime series dataLikelihood formulationBayesian methodsEquivalent resultsBayesian analysisCase-crossoverBayesian frameworkNonlinear Modeling and Processing Using Empirical Intrinsic Geometry with Application to Biomedical Imaging
Talmon R, Shkolnisky Y, Coifman R. Nonlinear Modeling and Processing Using Empirical Intrinsic Geometry with Application to Biomedical Imaging. Lecture Notes In Computer Science 2013, 8085: 441-448. DOI: 10.1007/978-3-642-40020-9_48.Peer-Reviewed Original ResearchNonlinear filtering problemInformation geometryFiltering problemDifferential geometryNonlinear filteringIntrinsic modelingIntrinsic geometryBayesian frameworkStatistical modelRandom observationsNonlinear modelingInstrumental modalitiesInferred modelGeometryNoise resilientReal signalsInvariantsModelingPhoton counterModelBiomedical imagingFilteringApplicationsProblem
2012
A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies
Bhadra D, Daniels M, Kim S, Ghosh M, Mukherjee B. A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies. Biometrics 2012, 68: 361-370. PMID: 22313248, PMCID: PMC3935236, DOI: 10.1111/j.1541-0420.2011.01686.x.Peer-Reviewed Original ResearchConceptsBayesian semiparametric approachSemiparametric approachCase-control studyReversible jump Markov chain Monte Carlo algorithmMarkov chain Monte Carlo algorithmMeasures of cumulative exposureLongitudinal biomarker informationMonte Carlo algorithmClinically meaningful estimatesSmooth functionsCase-control study of prostate cancerWeighted integralsCumulative exposureInfluence functionJoint likelihoodLikelihood formulationExposure historyStudy of prostate cancerDisease risk modelsHierarchical Bayesian frameworkDisease statusBayesian frameworkCase-controlRisk modelCohort study
2011
Bayesian Time-Series Analysis of a Repeated-Measures Poisson Outcome With Excess Zeroes
Murphy TE, Van Ness PH, Araujo KL, Pisani MA. Bayesian Time-Series Analysis of a Repeated-Measures Poisson Outcome With Excess Zeroes. American Journal Of Epidemiology 2011, 174: 1230-1237. PMID: 22025357, PMCID: PMC3254157, DOI: 10.1093/aje/kwr252.Peer-Reviewed Original ResearchConceptsPosterior predictive simulationsExcess zerosBayesian modelBayesian time series analysisPredictive simulationsHierarchical Bayesian modelPoisson outcomesPosterior distributionTime series analysisBayesian frameworkRelated resultsStatistical factorsBayesian analysisRandom effects Poisson modelFrequentistZerosPoisson modelSmall samplesExcessive numberAutocorrelationSimulationsTime series techniquesModelPeriodicity
2009
Segmentation of the Left Ventricle from Cardiac MR Images Using a Subject-Specific Dynamical Model
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. Segmentation of the Left Ventricle from Cardiac MR Images Using a Subject-Specific Dynamical Model. IEEE Transactions On Medical Imaging 2009, 29: 669-687. PMID: 19789107, PMCID: PMC2832728, DOI: 10.1109/tmi.2009.2031063.Peer-Reviewed Original ResearchConceptsSubject-specific dynamical modelGeneric dynamical modelDynamical modelStatistical modelSpecific dynamical modelRecursive Bayesian frameworkDynamic prediction algorithmStatic modelBayesian frameworkCardiac sequenceMotion modelActive Appearance Motion ModelsError propagationSpecific motion patternsPeriodic natureExperimental resultsPropagationCardiac shapeSegmentation resultsBackward directionSequential segmentationDynamicsModelMotion patternsOne-outA Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography. Lecture Notes In Computer Science 2009, 5761: 206-213. PMID: 20054422, PMCID: PMC2801876, DOI: 10.1007/978-3-642-04268-3_26.Peer-Reviewed Original ResearchSubject-specific dynamical modelCurrent frameMotion patternsRecursive Bayesian frameworkSegmentation taskPast framesAutomatic segmentationPrevious frameSegmentation processShape priorsLV segmentationManual segmentationSegmentationIntensity informationCardiac sequenceEchocardiographic sequencesStatic modelPrior knowledgeTemporal coherenceDynamical shape priorsCardiac motionCardiac modelsBayesian frameworkGeneric dynamical modelEchocardiographic imagesA dynamical shape prior for LV segmentation from RT3D echocardiography.
Zhu Y, Papademetris X, Sinusas AJ, Duncan JS. A dynamical shape prior for LV segmentation from RT3D echocardiography. 2009, 12: 206-13. PMID: 20425989, PMCID: PMC7814293.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceComputer SimulationComputer SystemsEchocardiography, Three-DimensionalHeart VentriclesHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalModels, AnatomicPattern Recognition, AutomatedPhantoms, ImagingReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSubject-specific dynamical modelCurrent frameMotion patternsRecursive Bayesian frameworkSegmentation taskPast framesAutomatic segmentationPrevious frameSegmentation processLV segmentationManual segmentationSegmentationIntensity informationCardiac sequenceEchocardiographic sequencesStatic modelPrior knowledgeTemporal coherenceCardiac motionCardiac modelsBayesian frameworkGeneric dynamical modelEchocardiographic imagesFrameInter-subject variability
2008
A Bayesian hierarchical model for the estimation of two incomplete surveillance data sets
Buenconsejo J, Fish D, Childs JE, Holford TR. A Bayesian hierarchical model for the estimation of two incomplete surveillance data sets. Statistics In Medicine 2008, 27: 3269-3285. PMID: 18314934, DOI: 10.1002/sim.3190.Peer-Reviewed Original ResearchConceptsBayesian hierarchical modelMarkov chain Monte Carlo simulation techniquesMonte Carlo simulation techniqueHierarchical modelModel uncertaintyUse of covariatesBayesian frameworkSimulation techniquesModel-based approachData setsSurveillance datasetModelSuch dataPublic health impactSpatial distributionPublic health officialsInferenceEstimationSpatial variationTreatable diseaseChronic diseasesUncertaintyHigh riskDisease riskDisease controlSegmentation of Left Ventricle from 3D Cardiac MR Image Sequences Using a Subject-Specific Dynamical Model
Zhu Y, Papademetris X, Sinusas A, Duncan JS. Segmentation of Left Ventricle from 3D Cardiac MR Image Sequences Using a Subject-Specific Dynamical Model. 2015 IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2008, 2008: 1-8. PMID: 20052308, PMCID: PMC2801445, DOI: 10.1109/cvpr.2008.4587433.Peer-Reviewed Original ResearchSubject-specific dynamical modelGeneric dynamical modelDynamical modelSpecific dynamical modelRecursive Bayesian frameworkStatic modelBayesian frameworkStatistical modelCardiac sequenceCardiac MR image sequencesModel-based segmentationSpecific motion patternsCardiac shapeMR image sequencesImage sequencesMotion patternsModelOne-outLocal consistencyCurrent frameExperimental resultsSegmentation resultsDynamicsPast framesInter-subject variability
2005
Semiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure
Sinha S, Mukherjee B, Ghosh M, Mallick B, Carroll R. Semiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure. Journal Of The American Statistical Association 2005, 100: 591-601. DOI: 10.1198/016214504000001411.Peer-Reviewed Original Research
2004
Bayesian Semiparametric Modeling for Matched Case–Control Studies with Multiple Disease States
Sinha S, Mukherjee B, Ghosh M. Bayesian Semiparametric Modeling for Matched Case–Control Studies with Multiple Disease States. Biometrics 2004, 60: 41-49. PMID: 15032772, DOI: 10.1111/j.0006-341x.2004.00169.x.Peer-Reviewed Original ResearchConceptsSemiparametric Bayesian frameworkBayesian semiparametric modelSemiparametric modelDirichlet processStratum effectsConditional likelihoodProbability of disease developmentBayesian approachNumerical integration schemeBayesian frameworkSample sizeDirichletActual estimationMLEMissingnessMarkovIntegration schemeExposure distributionBayesianEstimationRegression modelsMultiple disease statesDistributionProbabilityDisease states
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply