Alexandros Sountoulidis

COSTE embeds spatial relationships into a hierarchical metric space to reveal tissue architecture in spatial omics data, identifying spatially defined cell states and disease-associated patterns.

Spapros selects optimal probe sets for targeted spatial transcriptomics to improve cell type identification and spatial variation detection across multiple datasets.

This study maps the spatial organization of the developing human lung using high-parametric protein imaging, revealing cell type composition and temporal changes across five developmental timepoints.

This study identifies an autocrine role for Hedgehog signaling in regulating epithelial cell proliferation and differentiation in the trachea.

The paper creates a comprehensive topographic atlas of early human lung development, identifying cell states, trajectories, and interactions to understand cell heterogeneity origins.

SCRINSHOT maps cell states in tissue sections at single-cell resolution, showing high correlation with scRNA-Seq data and enabling detailed spatial analysis of cell types.