DeepDR: a deep learning library for drug response prediction.

ABSTRACT:

Summary

Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have shown promise in predicting drug response; however, the lack of convenient tools to support such modeling limits their widespread application. To address this, we introduce DeepDR, the first DL library specifically developed for drug response prediction. DeepDR simplifies the process by automating drug and cell featurization, model construction, training, and inference, all achievable with brief programming. The library incorporates three types of drug features along with nine drug encoders, four types of cell features along with nine cell encoders, and two fusion modules, enabling the implementation of up to 135 DL models for drug res

SUBMITTER: Jiang Z 

PROVIDER: S-EPMC11629690 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature