5 papers
Markov Neighborhood Regression for High-Dimensional Inference
Faming Liang, Jingnan Xue, Bochao Jia
This paper proposes an innovative method for constructing confidence intervals and assessing p-values in statistical inference for high-dimensional linear models. The proposed meth…
Learning Gene Regulatory Networks with High-Dimensional Heterogeneous Data
Bochao Jia, Faming Liang
The Gaussian graphical model is a widely used tool for learning gene regulatory networks with high-dimensional gene expression data. Most existing methods for Gaussian graphical mo…
Mixture Envelope Model for Heterogeneous Genomics Data Analysis
Bochao Jia
Envelope model also known as multivariate regression model was proposed to solve the multiple response regression problems. It measures the linear association between predictors an…
Fast Bayesian Integrative Learning of Multiple Gene Regulatory Networks for Type 1 Diabetes
Bochao Jia, Faming Liang, the TEDDY Study Group
Motivated by the need to study the molecular mechanism underlying Type 1 Diabetes (T1D) with the gene expression data collected from both the patients and healthy controls at multi…
An Imputation-Consistency Algorithm for High-Dimensional Missing Data Problems and Beyond
Faming Liang, Bochao Jia, Jingnan Xue +2
Missing data are frequently encountered in high-dimensional problems, but they are usually difficult to deal with using standard algorithms, such as the expectation-maximization (E…