A biomedical open knowledge network harnesses the power of AI to understand deep human biology

Abstract

Knowledge representation and reasoning (KR&R) has been successfully implemented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article, we describe concrete uses of Scalable PrecisiOn Medicine Knowledge Engine (SPOKE), an open knowledge network that connects curated information from thirty-seven specialized and humancurated databases into a single property graph, with 3 million nodes and 15 million edges to date. Applications discussed in this article include drug discovery, COVID-19 research and chronic disease diagnosis, and management.

Specimen, biological structure, and spatial ontologies in support of a Human Reference Atlas

“…A series of qualitatively new use cases will be developed to showcase the value of combining HRA with other LOD data—e.g, from the Gene-Centric Common Fund Data Ecosystem (CFDE) Knowledge Graph ( https://maayanlab.cloud/gene-kg/downloads ), the STRING - Protein-Protein Interaction Networks Functional Enrichment Analysis database ( https://string-db.org/ ), and the Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) graph database ( https://cns-iu.github.io/spoke-vis/home ), which federates more than 30 open datasets into a public data commons of health-relevant knowledge 13 .…”

“…It thus provides a unifying vocabulary for HRA construction and usage—making it possible to ingest external data sources; supporting uniform tissue sample registration that includes the spatial positioning and semantic annotations within the 3D reference organs; and supporting user-formulated cross-domain queries over tissue donor properties, anatomical structures, cell types, biomarkers, and 3D space. The use of the CCF Ontology as a framework for the HRA makes it possible to publish HRA data in the Linked Open Data (LOD) cloud 13 in a Findable, Accessible, Interoperable and Reusable (FAIR) 5 manner; the CCF API supports programmatic access to HRA data. We provide templates via data specifications so that other consortia can easily publish their data in a HRA-compatible manner.…”

Specimen, Biological Structure, and Spatial Ontologies in Support of a Human Reference Atlas

“…It thus provides a unifying vocabulary for HRA construction and usage-making it possible to ingest external data sources; supporting uniform tissue sample registration that includes the spatial positioning and semantic annotations within the 3D reference organs; and supporting user-formulated cross-domain queries over tissue donor properties, anatomical structures, cell types, biomarkers, and 3D space. The CCFO makes it possible to publish HRA data in the Linked Open Data (LOD) cloud 16 in a Findable, Accessible, Interoperable and Reusable (FAIR) 17 manner; the CCF API supports programmatic access to HRA data. We provide templates via data specifications so that other consortia can easily publish their data in a HRA-compatible manner.…”

“…A series of qualitatively new use cases will be developed to showcase the value of combining HRA with other LOD data—e.g, from the Gene-Centric Common Fund Data Ecosystem (CFDE) Knowledge Graph 67 , the STRING - Protein-Protein Interaction Networks Functional Enrichment Analysis database 68 , and the Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) graph database that federates more than 30 open datasets into a public data commons of health relevant knowledge 16,69 .…”

Knowledge graphs: Introduction, history, and perspectives

“…For example, the precision medicine OKN reported later in this special volume makes an extensive use of the graph‐based visualization and inference for solving problems in biomedicine (Baranzini et al. 2022).…”