Lars Grasedyck

This study introduces metMHN, a model to infer metastatic progression from cross-sectional cancer genomics data, identifying TP53 and EGFR as key mediators and highlighting copy number alterations in post-seeding adaptation.

This paper extends cancer progression models to account for observation bias by modeling how genetic events affect tumor detection, improving the accuracy of inferred causal interactions.