A new Gaussian graphical model that produces subject-specific and predictive graphs with theoretical guarantee.
Bayesian federated learning.
Graphical Dirichlet process.
A new Gaussian graphical model that produces subject-specific and predictive graphs with theoretical guarantee.
The successful development and implementation of precision immuno-oncology therapies requires a deeper understanding of the immune architecture at a patient level. T-cell Receptor (TCR) repertoire sequencing is a relatively new technology that …
Bayesian integrative matrix factorization.
A Bayesian hierarchical varying-sparsity regression (BEHAVIOR) model that selects clinically relevant disease markers by integrating proteogenomic and clinical data.
A new directed acyclic graphical model that produces subject-specific and predictive graphs with theoretical guarantee.
A hierarchical reciprocal graphical models to infer gene networks from heterogeneous data with or without known groups.
A Gaussian reciprocal graphical model for inference about gene regulatory relationships by integrating mRNA gene expression and DNA level information including copy number and methylation.
An array-variate directed acyclic graphical model for tensor data.
An integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient’s clinical outcome.