Leveraging multi-omic data for integrative exploratory, predictive, and network analyses

A randomized pairwise likelihood method for complex statistical inferences

Leveraging multi-omic data for integrative exploratory, predictive, and network analyses

Multi-omic integration for enhanced interpretability in exploratory analyses

Mixture models as a useful tool for identifying co-expressed genes from RNA-seq data with coseq

Integrative and interactive analyses of multi-omics data

Individualized multi omic pathway deviation scores using multiple factor analysis

Exploring drivers of gene expression in The Cancer Genome Atlas

HDR defense presentation