Heather A. Harrington

The paper introduces scDIV, a robust diversity measure for single-cell and spatial transcriptomics data that is insensitive to clustering parameters and evaluates its application in developmental datasets.

The paper develops a universal imaging phenome using SAM features and SPOT tool, showing it outperforms deep learning models in capturing dynamic cell behaviors.

This study uses topological data analysis to quantify ECM architecture and spatial patterns in lung adenocarcinoma, revealing progressive changes linked to immune exclusion and metabolic shifts.