Nanne Aben

The paper presents a large-scale cancer pharmacogenomic screen with 11,576 experiments on 910 drug combinations across 85 cancer cell lines, enabling crowd-sourced prediction of synergistic drug pairs and biomarkers.

The paper uses multi-task learning to identify biomarkers of anti-cancer drug synergy using low-sample-size drug combination data from 85 cell lines and 167 drug combinations.

iTOP infers relationships between omics datasets using partial matrix correlations and identifies gene expression as a mediator between other datasets and drug response.

The paper quantifies proteomic and genomic variation in colorectal cancer cell lines to understand how mutations affect protein levels and drug responses.