Uno

Unified Drug Response Predictor

Model Architecture

UNO consists of two fully connected neural network branches for separately embedding the drug and cell line features, then a third fully connected neural network to regress on the combined embedded features. UNO was one of the benchmark models in the CANDLE project for cancer drug response.

Feature Representation

• Cancer features:

  • Gene Expression: as floats

• Drug features:

  • Drug Molecular Descriptors: mordred values as floats

URLs

• Original GitHub

References

1. F. Xia, et. al. “A cross-study analysis of drug response prediction in cancer cell lines”, Briefings in Bioinformatics, 2022