Integrative factor-adjusted sparse generalized linear models
Xu F, Ma S, Zhang Q. Integrative factor-adjusted sparse generalized linear models. Journal Of Statistical Computation And Simulation 2024, 95: 764-780. DOI: 10.1080/00949655.2024.2439450.Peer-Reviewed Original ResearchVariable selection consistencyHigh-dimensional dataIncreased accessibility of dataSelection consistencyConsistency propertiesCorrelated covariatesGeneralized linear modelVariable selectionAnalysis of genetic dataAccessibility of dataIdiosyncratic componentsCompetitive performanceCovariatesGenetic dataLinear modelSample sizeImprove model performanceEstimationIntegrated analysisModel estimatesLatent factorsModel performancePractical useConsistencyA penalized integrative deep neural network for variable selection among multiple omics datasets
Li Y, Ren X, Yu H, Sun T, Ma S. A penalized integrative deep neural network for variable selection among multiple omics datasets. Quantitative Biology 2024, 12: 313-323. DOI: 10.1002/qub2.51.Peer-Reviewed Original ResearchOmics data analysisAvailability of omics dataMultiple omics datasetsGene expression datasetsAggregate multiple datasetsDeep neural networksOmics dataIntegrated deep neural networkOmics datasetsExpression datasetsMultiple datasetsDeep learningDiverse originsNeural networkOmicsAbstract Deep learningVariable selection resultsSample sizeVariable selectionIntegrated analysis frameworkCognitive statusOvarian cancer patientsModel interpretationExtensive simulation studyDataset
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