Adriaan P. IJzerman

The paper maps protein-protein interactions of 396 SLC transporters using interaction proteomics and functional assays, providing a resource for understanding SLC function and drug targeting.

This paper introduces a knowledge graph to prioritize cancer mutations for targeted therapy by integrating clinical, functional, and structural data.

This study analyzes somatic mutations in GPCRs across cancer patients and healthy individuals, identifying conserved mutation hotspots and prioritizing GPCRs for further cancer research.

This study compares machine learning methods on a standardized ChEMBL dataset, finding deep neural networks outperform conventional methods in bioactivity prediction.