Duong H.T. Vo

This paper develops a sparse inverse covariance matrix estimation framework for scRNA-seq data to capture direct gene interactions, showing improved performance in high-dimensional and zero-inflated data.

This paper introduces a Bayesian mixture model to identify cell sub-populations in single-cell RNA-seq data, addressing zero-inflation and providing uncertainty estimates in cluster assignments.

The paper identifies immune cell-specific gene networks associated with response to nivolumab therapy in melanoma and highlights B cell genes as potential prognostic biomarkers.