2022
Bayesian network mediation analysis with application to the brain functional connectome
Zhao Y, Chen T, Cai J, Lichenstein S, Potenza M, Yip S. Bayesian network mediation analysis with application to the brain functional connectome. Statistics In Medicine 2022, 41: 3991-4005. PMID: 35795965, PMCID: PMC10131252, DOI: 10.1002/sim.9488.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremBrainConnectomeHumansMagnetic Resonance ImagingMediation AnalysisNerve NetConceptsStochastic block modelBayesian paradigmBrain functional connectomeBlock modelConnectivity weightsFunctional connectomeNetwork measurementsEffect componentApproach applicationBlock allocationOpioid abstinenceAnalytic approachNetwork neurosciencePractical illustrationTherapeutic interventionsMediation analysisNeural circuitsNetwork structureBrain functioningMediatorsFunctional networksFeature selectionApplicationsModelNetworkBayesian Interaction Selection Model for Multimodal Neuroimaging Data Analysis
Zhao Y, Wu B, Kang J. Bayesian Interaction Selection Model for Multimodal Neuroimaging Data Analysis. Biometrics 2022, 79: 655-668. PMID: 35220581, PMCID: PMC9418386, DOI: 10.1111/biom.13648.Peer-Reviewed Original Research
2021
Bayesian network-driven clustering analysis with feature selection for high-dimensional multi-modal molecular data
Zhao Y, Chang C, Hannum M, Lee J, Shen R. Bayesian network-driven clustering analysis with feature selection for high-dimensional multi-modal molecular data. Scientific Reports 2021, 11: 5146. PMID: 33664338, PMCID: PMC7933297, DOI: 10.1038/s41598-021-84514-0.Peer-Reviewed Original ResearchConceptsMolecular dataJoint posterior distributionHigh-dimensional settingsVariational Bayes approachSingle-cell dataArt clustering methodsPosterior distributionMolecular profiling dataComputational efficiencyCanonical oncogenicTranscriptomic alterationsBiological discoveryModel inferenceBayes approachCell decompositionStemness phenotypeProfiling dataSingle cellsComputational methodsBulk tumorPathway alterationsNebulaClustering methodAnalysis settingsCell data
2020
Bayesian sparse heritability analysis with high-dimensional neuroimaging phenotypes
Zhao Y, Li T, Zhu H. Bayesian sparse heritability analysis with high-dimensional neuroimaging phenotypes. Biostatistics 2020, 23: 467-484. PMID: 32948880, PMCID: PMC9308456, DOI: 10.1093/biostatistics/kxaa035.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseBayes TheoremHumansNeuroimagingPhenotypePolymorphism, Single NucleotideConceptsHeritability analysisHuman complex traitsLarge-scale phenotypeQuantitative geneticsComplex traitsPhenotypic variationTrait selectionGenetic datasetsSingle phenotypeDownstream analysisGenetic contributionHeritability estimationPhenotypeTraitsCentral roleNeuroimaging phenotypesUnited Kingdom BiobankHierarchical selectionPhenotypic methodsGeneticsHeritabilitySelectionVariationBrain variation