Peter Bühlmann

Drug-Prot quantifies drug effects and interactions using proteomic data, revealing protein-level causal relationships and actionable drug combinations.

This paper introduces SBB principles to evaluate virtual cell perturbation models, showing that complex methods often fail to outperform simple baselines.

This paper introduces a method to detect dysregulated signaling pathways in cancer by comparing normal and cancerous cells using causal inference, showing improved performance over existing methods.

The paper uses multi-omics data from mice to identify gene-environment-age interactions and causal molecular networks linked to longevity.