Patrick Glen Pilie

PerturbLDM predicts single-cell transcriptional responses to perturbations using a latent diffusion model, outperforming existing methods in drug-dose-cell line combinations and capturing key biological programs.

This study shows KDM6A mutations in bladder cancer improve response to immune checkpoint therapy but worsen chemotherapy outcomes through effects on DNA repair and metabolic reprogramming.

scEMB is a transformer-based model that learns gene embeddings from single-cell transcriptomics data, outperforming existing models in tasks like clustering and cell type annotation.