Zhenke Wu

The paper introduces a Bayesian probabilistic framework to infer treatment trees from PDX data, identifying synergistic treatment combinations and their biological mechanisms across cancers.

The paper develops a tree-structured shrinkage method for latent class analysis that integrates sample similarities to improve class probability estimation.

The paper develops a Bayesian method for clustering multivariate binary data with scientific constraints, showing improved interpretability and clustering performance in protein data analysis.

This study uses polygenic risk scores (PRS) for cancers in a phenome-wide association study (PheWAS) to identify associations with multiple phenotypes, finding significant links to both cancer and non-cancer diagnoses.