Machine learning-based prediction of response to PARP inhibition across cancer types.
Katherine E. Hill, Ahmed Rattani, Christopher E. Lietz, Cassandra C. Garbutt, Edwin Choy, Gregory Michael Cote, Aedín C. Culhane, Andrew D. Kelly, Benjamin Haibe‐Kains, Dimitrios Spentzos
The paper develops a multi-gene signature predicting PARP inhibitor response across cancer types using machine learning and validates it in vitro and in clinical datasets.
medRxiv · Sep 27, 2019 · PreprintGenetic & Genomic Medicine