Nallala Hima Varshini

Abstract High-level screening technologies have generated a vast volume of drug-sensitivity data for a panel of cancer cell lines and hundreds of chemicals. By identifying molecular genetic factors of drug sensitivity and developing novel anticancer medicines, computational approaches to analysing these data can assist in the development of anticancer therapies. Conventional deep learning models lack the ability to select the best imputation strategy or to handle missing values.