Pages that link to "Item:Q3576923"

The following pages link to Incorporating Predictor Network in Penalized Regression with Application to Microarray Data (Q3576923):

Displaying 34 items.

• Marginal empirical likelihood and sure independence feature screening (Q385789) (← links)
• A Bayesian nonparametric mixture model for selecting genes and gene subnetworks (Q400643) (← links)
• Support vector machines with disease-gene-centric network penalty for high dimensional microarray data (Q440098) (← links)
• Selecting massive variables using an iterated conditional modes/medians algorithm (Q491389) (← links)
• The sparse Laplacian shrinkage estimator for high-dimensional regression (Q651021) (← links)
• Incorporating biological information into linear models: a Bayesian approach to the selection of pathways and genes (Q652363) (← links)
• Incorporating grouping information in Bayesian variable selection with applications in genomics (Q899018) (← links)
• Network-based feature screening with applications to genome data (Q1624846) (← links)
• Incorporating spatial structure into inclusion probabilities for Bayesian variable selection in generalized linear models with the spike-and-slab elastic net (Q2059435) (← links)
• On integer and MPCC representability of affine sparsity (Q2294300) (← links)
• Bayesian network marker selection via the thresholded graph Laplacian Gaussian prior (Q2297232) (← links)
• GenePEN: analysis of network activity alterations in complex diseases via the pairwise elastic net (Q2344261) (← links)
• IPF-LASSO: integrative \(L_1\)-penalized regression with penalty factors for prediction based on multi-omics data (Q2405418) (← links)
• Graph-based sparse linear discriminant analysis for high-dimensional classification (Q2418517) (← links)
• Graph structured sparse subset selection (Q2662712) (← links)
• Network-based penalized regression with application to genomic data (Q2861942) (← links)
• Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information (Q3119840) (← links)
• miRNA–target gene regulatory networks: A Bayesian integrative approach to biomarker selection with application to kidney cancer (Q3459940) (← links)
• A Hierarchical Semiparametric Model for Incorporating Intergene Information for Analysis of Genomic Data (Q4911942) (← links)
• (Q4969131) (← links)
• Sparse linear discriminant analysis in structured covariates space (Q4970230) (← links)
• (Q4986376) (← links)
• A link-free sparse group variable selection method for single-index model (Q5138715) (← links)
• Joint Bayesian Variable and DAG Selection Consistency for High-dimensional Regression Models with Network-structured Covariates (Q5155198) (← links)
• Simultaneous Grouping Pursuit and Feature Selection Over an Undirected Graph (Q5327299) (← links)
• An overview of techniques for linking high‐dimensional molecular data to time‐to‐event endpoints by risk prediction models (Q5391149) (← links)
• Leveraging external knowledge on molecular interactions in classification methods for risk prediction of patients (Q5391151) (← links)
• A significance test for graph‐constrained estimation (Q5739274) (← links)
• High-dimensional expectile regression incorporating graphical structure among predictors (Q5887973) (← links)
• A selective review of group selection in high-dimensional models (Q5965305) (← links)
• Identifying Brain Hierarchical Structures Associated with Alzheimer's Disease Using a Regularized Regression Method with Tree Predictors (Q6079719) (← links)
• Identifying important gene signatures of BMI using network structure-aided nonparametric quantile regression (Q6617521) (← links)
• Incorporating Graphical Structure of Predictors in Sparse Quantile Regression (Q6617798) (← links)
• Feature selection and classification over the network with missing node observations (Q6626779) (← links)