1146-Emergent Tissue Properties from Spatial Profiles

Paper Talk · Jun 18, 2026 · 23m

This research evaluates the capacity of Graph Neural Networks (GNNs) to predict tissue phenotypes by analyzing the spatial organization and molecular profiles of cells. By modeling tissues as spatial graphs, the study demonstrates that while GNNs may not always outperform simpler models on small datasets, they successfully capture clinically relevant features and continuous biological trajectories, such as the progression of tumor grades. The authors utilize an ablation study to compare the predictive power of spatial context against single-cell and bulk representations across colorectal and…