Disease-Gene link prediction using Pytorch Geometric

Reproduced from Disease-Gene Interactions with Graph Neural Networks and Graph Autoencoders

Paper: Towards Probabilistic Generative Models Harnessing Graph Neural Networks for Disease-Gene Prediction

Create conda env

conda env create -f environment.yml
conda activate gene_disease

Run VGAE and make predictions

python src\train_vgae.py

Further reading

1. https://medium.com/@sunil7545/variational-autoencoders-ce7fe921cce7
2. https://medium.com/@sunil7545/kl-divergence-js-divergence-and-wasserstein-metric-in-deep-learning-995560752a53
3. geneDRAGNN: Gene Disease Prioritization using Graph Neural Networks
4. linear algebra (https://datahacker.rs/dot-product-inner-product), (https://datahacker.rs/category/linear-algebra/page/3/)