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.

Model Type

Regression

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