Skip to content

References: Biomedical Knowledge Graphs and Ontologies

  1. Gene Ontology - Wikipedia - Describes the Gene Ontology project providing structured vocabulary for gene functions across three domains: molecular function, biological process, and cellular component, organized as a directed acyclic graph.

  2. Knowledge Graph - Wikipedia - Overview of knowledge graph concepts including entity-relationship modeling, graph embeddings, and applications in information retrieval, with relevance to biomedical data integration.

  3. Graph Neural Network - Wikipedia - Explains graph neural network architectures including message passing, graph convolutional networks, and graph attention networks used for node classification and link prediction in biological graphs.

  4. The Gene Ontology Handbook - Christophe Dessimoz - Humana Press - Practical guide to using the Gene Ontology covering annotation practices, enrichment analysis, semantic similarity measures, and ontology structure navigation for bioinformatics research.

  5. Graph Representation Learning - William Hamilton - Morgan and Claypool - Comprehensive treatment of graph embedding methods including node2vec, knowledge graph embeddings, and graph neural networks applicable to biomedical knowledge graph analysis.

  6. Gene Ontology Documentation - Gene Ontology Consortium - Official documentation covering GO term structure, annotation evidence codes, enrichment analysis tools, and the GO API for programmatic access to ontology data.

  7. OBO Foundry - OBO Foundry - Registry of interoperable biomedical ontologies following shared design principles, including ontologies for anatomy, phenotype, disease, and chemical entities used in knowledge graph construction.

  8. PyKEEN Documentation - PyKEEN - Documentation for the Python library for knowledge graph embeddings, covering TransE, RotatE, and other embedding models used for link prediction in biomedical knowledge graphs.

  9. Hetionet - Hetionet Project - Open-source biomedical knowledge graph integrating 47,031 nodes and 2,250,197 edges across genes, diseases, compounds, and pathways, demonstrating knowledge graph applications in drug repurposing.

  10. DGL-KE: Knowledge Graph Embedding Library - Deep Graph Library - Documentation for the distributed knowledge graph embedding library, covering training of TransE, DistMult, and ComplEx models on large-scale biomedical knowledge graphs.