📣 Drug-Drug-Synergy model (DDoS) 💊

This repository contains the code for the DDoS model implementation with PyTorch.

DDoS is a Graph Neural Network (GNN) based neural network model used for drug-drug-cell line synergy predictions.

Publication

Schwarz, Kyriakos, et al. “DDoS: A Graph Neural Network based Drug Synergy Prediction Algorithm.” arXiv preprint arXiv:2210.00802 (2022), https://arxiv.org/abs/2210.00802.

Installation

• git clone the repo and cd into it.
• Optionally, create a python virtualenv and install inside the pip packages from the requirements.txt file. Note that torch and CUDA versions depend on the GPU/CUDA which you use locally.

Data Download

Download Gene Expression data (link: 1) and Drug Combination data (link: 2). Place them into the data/preprocessing directory.

Running 🏃

1. use notebooks/DDoS_Preprocessing.ipynb and notebooks/DDoS_Dataset_Generation.ipynb to generate DataTensors from the drug combination features (chemical structures and gene expression).
2. use notebooks/DDoS-Hyperparam.ipynb to find the best performing model hyperparameters.
3. use notebooks/DDoS_Train_Eval.ipynb to train / test on the best analyze the results.