Irene Li

Eva is a foundation model for tissue imaging data that learns multi-scale spatial representations and performs various tasks like cross-modal inference and patient stratification.

The paper introduces the colocatome, a spatial-omic framework, to compare microenvironment features between tumour-stroma assembloids and lung cancer specimens, finding that fibroblasts protect cancer cells from treatment by reorganizing cytoarchitecture.

The paper introduces REMI, a graph-based method to reconstruct cell-cell interactions in lung adenocarcinoma by accounting for ligand-receptor dependencies, and validates its findings experimentally.

CELESTA identifies cell types in multiplexed in situ images by integrating protein expression and spatial information, revealing novel spatial biology associated with lymph node metastasis.