Bastian Pfeifer

Ensemble-GNN enables federated, ensemble-based graph neural networks for disease module discovery using patient-specific PPI networks and omics data.

CLARUS is an interactive explainable AI platform for GNNs that allows clinicians to validate, modify, and retrain models using patient-specific biological networks.

This paper introduces GNN-SubNet, an explainable graph neural network framework for detecting disease subnetworks using patient-specific protein-protein interaction networks enriched with molecular data.

This paper introduces HC-fused, a hierarchical clustering and data fusion method for disease subtype discovery, showing superior performance on cancer data from TCGA.

The paper introduces kNN-based genome-scan methods for detecting selection and introgression, showing strong performance across various parameters.

The paper introduces a new statistic, Bdf, to detect and quantify introgression by combining dxy and Pattersons D, and integrates it into the PopGenome R-package.