# BADGER: biologically-aware interpretable differential gene expression ranking model

## TL;DR

BADGER is a model that predicts how drugs affect gene expression in cancer cells, helping find new drug uses by considering biological pathways and cell similarities.

## Contribution

BADGER introduces an interpretable model for differential gene expression ranking with pathway-based drug target integration and similarity-based embeddings for novel cell lines.

## Key findings

- BADGER outperforms baselines in predicting gene expression changes for both new cell lines and untested drug-cell combinations.
- The model integrates pathway information and uses attention blocks to enhance explainability and capture drug effects.
- BADGER enables robust predictions for drug repurposing by leveraging similarities across diseases and cell lines.

## Abstract

Understanding which genes are significantly affected by drugs is crucial for drug repurposing, as drugs targeting specific pathways in one disease might be effective in another with similar genetic profiles. By analyzing gene expression changes in cells before and after drug treatment, we can identify the genes most impacted by drugs.

The Biologically-Aware Interpretable Differential Gene Expression Ranking (BADGER) model is an interpretable model designed to predict gene expression changes resulting from interactions between cancer cell lines and chemical compounds. The model enhances explainability through integration of prior knowledge about drug targets via pathway information, handles novel cancer cell lines through similarity-based embedding, and employs three attention blocks that mimic the cascading effects of chemical compounds. This model overcomes previous limitations of cell line range and explainability constraints in drug–cell response studies. The model demonstrates superior performance over baselines in both unseen cell and unseen pair split evaluations, showing robust prediction capabilities for untested drug–cell line combinations.

This makes it particularly valuable for drug repurposing scenarios, especially in developing therapeutic plans for new or resistant diseases by leveraging similarities with other diseases. All code and data used in this study are available at https://github.com/dmis-lab/BADGER.git.