More details
1) Outputs a drug ranking prediction based on a chosen disease and embedding model. 2) Includes the outcomes of predictions on specific diseases generated by trained embedding models using the DRKG dataset. 3) Trains an embedding model on a given dataset. Predictions can be performed on the results of this training. 4) Performs predictions on the already trained embedding models.
See owner's GitHub Repo for more information: https://github.com/dlopezyse/Drug-Repurposing-using-KGE/tree/main
This work is based on the paper: Drug Repurposing Using Knowledge Graph Embeddings with a Focus on Vector-Borne Diseases: A Model Comparison as developed by Diego López Yse and Diego Torres for the Conference on Cloud Computing, Big Data & Emerging Topics 2023.
This application was not uploaded by the author, but through their publicly available Github repository (https://github.com/dlopezyse/Drug-Repurposing-using-KGE/tree/main).
MIT License
Copyright (c) 2023 Diego Lopez Yse
Warning: Not intended for clinical use. Assume outputs are unsafe and unvalidated. Use carefully.
- Drug Discovery & Development