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

<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds - Embeddings (v1.0.0)</strong></p><p><strong>Build Date:&nbsp;September 03, 2019</strong></p><blockquote><p>Please note that all resources linked below redirect to a publicly Google Cloud Storage bucket where all data are publicly accessible. Routing users from this wiki page is perfectly safe and allows us to avoid requiring users to have a Google account and login to download data. If you have any questions or concerns, please email the project maintainer at&nbsp;<a href="https://github.com/callahantiff/PheKnowLator/wiki/callahantiff@gmail.com">callahantiff@gmail.com</a>.</p></blockquote><p>The KG Benchmark Builds can also be downloaded from Zenodo:<br>👉&nbsp;<strong>KGs:</strong>&nbsp;<a href="https://doi.org/10.5281/zenodo.7030200">https://doi.org/10.5281/zenodo.7030200</a><br>👉&nbsp;<strong>Embeddings:</strong>&nbsp;<a href="https://zenodo.org/record/7030189">https://zenodo.org/record/7030189</a></p><p>&nbsp;</p><p>A&nbsp;<a href="https://github.com/xgfs/deepwalk-c">modified&nbsp;version</a> of the&nbsp;<a href="https://github.com/phanein/deepwalk">DeepWalk algorithm</a>&nbsp;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&nbsp;<a href="https://github.com/callahantiff/PheKnowLator/wiki/v1.0.0/figure-2-t-sne-plot-of-molecular-mechanisms">Figure</a>. 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&nbsp;with&nbsp;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).</p>