David S. DeLuca

Extending the capabilities of deconvolution to provide cell type specific pathway analysis of bulk RNA-seq data for idiopathic pulmonary fibrosis

This paper applies deconvolution to bulk RNA-seq data from idiopathic pulmonary fibrosis to identify cell-type specific pathway changes.

A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data

This study introduces a prior-informed VAE for transcriptome data that improves interpretability by learning latent features aligned with biological pathways.