Dr.VAE: improving drug response prediction via modeling of drug perturbation effects.

ABSTRACT:

Motivation

Individualized drug response prediction is a fundamental part of personalized medicine for cancer. Great effort has been made to discover biomarkers or to develop machine learning methods for accurate drug response prediction in cancers. Incorporating prior knowledge of biological systems into these methods is a promising avenue to improve prediction performance. High-throughput cell line assays of drug-induced transcriptomic perturbation effects are a prior knowledge that has not been fully incorporated into a drug response prediction model yet.

Results

We introduce a unified probabilistic approach, Drug Response Variational Autoencoder (Dr.VAE), that simultaneously models both drug response in terms of viability and transcriptomic perturbations. Dr.VAE is a deep

SUBMITTER: Rampasek L 

PROVIDER: S-EPMC6761940 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature