Bayesian robust learning in chain graph models for integrative pharmacogenomics
type: Item
instance of: scholarly article
title: Bayesian robust learning in chain graph models for integrative pharmacogenomics
author: Moumita Chakraborty
author: Veerabhadran Baladandayuthapani
author: Anindya Bhadra
author: Min Jin Ha
published in: The Annals of Applied Statistics
publication date: 2025-01-17T00:00:00Z
Mathematics Subject Classification ID: 62Pxx
zbMATH DE Number: 7969344
zbMATH Keywords: Bayesian graphical models
zbMATH Keywords: cancer
zbMATH Keywords: data integration
zbMATH Keywords: multiplatform genomics
zbMATH Keywords: pharmacogenomics
zbMATH Keywords: robust graphical models
MaRDI profile type: Publication
cites work: Alternative Markov properties for chain graphs
cites work: Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis
cites work: Inferring network structure in non-normal and mixed discrete-continuous genomic data
cites work: Posterior graph selection and estimation consistency for high-dimensional Bayesian DAG models
cites work: Structural learning and estimation of joint causal effects among network-dependent variables
cites work: Objective Bayes Covariate‐Adjusted Sparse Graphical Model Selection
cites work: Hyper Markov laws in the statistical analysis of decomposable graphical models
cites work: Copula Gaussian graphical models and their application to modeling functional disability data
cites work: Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property
cites work: A SINful approach to Gaussian graphical model selection
cites work: Robust graphical modeling of gene networks using classical and alternative \(t\)-distributions
cites work: Robust Bayesian graphical modeling using Dirichlet \(t\)-distributions
cites work: Sparse inverse covariance estimation with the graphical lasso
cites work: Bayesian Structure Learning in Multilayered Genomic Networks
cites work: Graphical models for associations between variables, some of which are qualitative and some quantitative
cites work: Joint mean-covariance estimation via the horseshoe
cites work: Penalized maximum likelihood estimation of multi-layered Gaussian graphical models
cites work: High-dimensional semiparametric Gaussian copula graphical models
cites work: The nonparanormal: semiparametric estimation of high dimensional undirected graphs
cites work: An introduction to copulas.
cites work: Efficient Bayesian inference for Gaussian copula regression models
cites work: Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
cites work: Regularized rank-based estimation of high-dimensional nonparanormal graphical models
cites work: A sparse conditional Gaussian graphical model for analysis of genetical genomics data
DOI: 10.1214/24-AOAS1936
description: scientific article; zbMATH DE number 7969344