PheKnowLator Human Disease Knowledge Graph Benchmarks Embeddings -- v1.0.0

RELEASE V1.0.0 KNOWLEDGE GRAPH EMBEDDING BENCHMARKS Build Type: v1.0.0 Knowledge Graph Embeddings Release: v1.0.0 Knowledge Graph Files: https://doi.org/10.5281/zenodo.7030200 A modified version of the DeepWalk algorithm was implemented to generate molecular mechanism embeddings from the biomedical knowledge graph. A t-SNE plot of the dimensionality reduced mechanism embeddings is shown in Figure 2. For this release, the hyperparameters were set to 512 dimensions, 100 walks, walk length of 20, and a window of 10. Two types of KGs were embedded: (1) the full KG; and (2) the full KG with deductive closure using the OWL 2 EL reasoner, ELK via Protégé v5.1.1. ELK is able to classify instances and supports inferences over class hierarchies and object properties. inference over disjointness, intersection, and existential quantification (ontology class hierarchies). Data Access: The word document in this repository (PheKnowLator_v1.0.0_Embeddings_Instructions.docx) contains details on the embeddings that were generated and how to download them. This project is licensed under Apache License 2.0 - see the LICENSE.md file for details. If you intend to use any of the information on this Wiki, please provide the appropriate attribution by citing this repository: @misc{callahan_tj_2019_3401437, author = {Callahan, TJ}, title = {PheKnowLator}, month = mar, year = 2019, doi = {10.5281/zenodo.3401437}, url = {https://doi.org/10.5281/zenodo.3401437} }