Recent technologies such as spatial transcriptomics, enable the measurement of gene expressions at the single-cell level along with the spatial locations of these cells in the tissue. Spatial clustering of the cells provides valuable insights into …
The equine gastrointestinal (GI) microbiome has been described in the context of various diseases. The observed changes, however, have not been linked to host function and therefore it remains unclear how specifc changes in the microbiome alter …
A new Gaussian graphical model that produces subject-specific and predictive graphs with theoretical guarantee.
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.