A Biomedical Open Knowledge Network Harnesses the Power of AI to Understand Deep Human Biology

Year: 2022

Type: article

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 SPOKE, an open knowledge network that connects curated information from 37 specialized and human-curated 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.

Source: AI Magazine

DOI: 10.1002/aaai.12037

Institutions: University of California, San Francisco, Indiana University Bloomington, Indiana University, Stanford Medicine, Stanford University, Lawrence Livermore National Laboratory, Institute for Systems Biology, San Diego Supercomputer Center, University of California San Diego

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $2,400

Funders: National Science Foundation, National Institutes of Health, National Center for Advancing Translational Sciences

Awards: A1: A Multi-Scale Open Knowledge Network for Biomedicine, EVIDARA: Automated Evidential Support from Raw Data for relay agents in Biomedical KG Queries

OpenAlex ID: W4223944906