Introduction

Additionally to the library, there is an example API, available at openpredict.semanticscience.org, for drug/disease predictions generated from the OpenPredict model.

The project is structured as follow:

• the code for the OpenPredict API endpoints in src/trapi/ defines:
  • a TRAPI endpoint returning predictions for the loaded models
  • individual endpoints for each loaded models, taking an input id, and returning predicted hits
  • endpoints serving metadata about runs, models evaluations, features for the OpenPredict model, stored as RDF, using the ML Schema ontology.
• various folders for different prediction models served by the OpenPredict API are available under src/:
  • the OpenPredict drug-disease prediction model in src/openpredict_model/
  • a model to compile the evidence path between a drug and a disease explaining the predictions of the OpenPredict model in src/openpredict_evidence_path/
  • a prediction model trained from the Drug Repurposing Knowledge Graph (aka. DRKG) in src/drkg_model/

The data used by the models in this repository is versionned using dvc in the data/ folder, and stored on DagsHub at dagshub.com/vemonet/translator-openpredict