Qizhen Lan

The paper introduces OCTAVE, a scale-resolved evaluation method for spatial gene expression prediction from histology, showing that fine-scale differences are missed by standard metrics.

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 paper develops MSCNet, a cross-modal generative model for reconstructing and restoring prostate MRI sequences, showing improved image quality and diagnostic performance in multicentre validation.