Kun‐Hsing Yu

RECON selects regions of interest from H&E images and reconstructs molecular profiles across entire slides at single-cell resolution for both transcriptomics and proteomics.

This paper introduces ReCLIP, a transformer-based framework that models protein-protein interactions at the residue level, showing high accuracy in predicting mutation effects and peptide-MHC binding.

SpatialCells automates the analysis of spatially resolved multiplexed single-cell data to characterize tumor microenvironments, enabling efficient feature extraction and downstream machine learning applications.