Emil Saucan

This study identifies gene modules associated with melanoma immunotherapy response using dynamic Ollivier-Ricci curvature analysis of gene expression data.

The paper analyzes dynamic gene expression data using a hypergraph model to quantify network heterogeneity and identifies differences in curvature between pluripotent stem cells, cancer cells, and pathways in melanoma.

This study applies graph Ricci curvatures to compare functional connectivity networks in ASD and typically developing individuals, finding region-specific differences associated with cognitive impairments and potential therapeutic targets.

This study uses Forman-Ricci curvature and network entropy to analyze gene networks and find correlations with cellular pluripotency and pathway robustness in stem cells and cancer cells.