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

Authors

  • Sergio E. Baranzini University of California San Francisco
  • Katy Börner Indiana University
  • John Morris University of California San Francisco
  • Charlotte A. Nelson University of California San Francisco
  • Karthik Soman University of California San Francisco
  • Erica Schleimer University of California San Francisco
  • Michael Keiser University of California San Francisco
  • Mark Musen Stanford University
  • Roger Pearce Lawrence Livermore National Laboratory
  • Tahsin Reza Lawrence Livermore National Laboratory
  • Brett Smith Institute for Systems Biology
  • Bruce W. Herr II Indiana University
  • Boris Oskotsky University of California San Francisco
  • Angela Rizk-Jackson University of California San Francisco
  • Katherine P. Rankin University of California San Francisco
  • Stephan J. Sanders University of California San Francisco
  • Riley Bove University of California San Francisco
  • Peter W. Rose University of California San Diego
  • Sharat Israni University of California San Francisco
  • Sui Huang Institute for Systems Biology

DOI:

https://doi.org/10.1002/aaai.12037

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 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.

The NSF Convergence Accelerator, by James Gary

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Published

2022-03-31

How to Cite

Baranzini, S. ., Börner, K. ., Morris, J. ., Nelson, C. ., Soman, K. ., Schleimer, E. ., Keiser, M. ., Musen, M. ., Pearce, R. ., Reza, T. ., Smith, B. ., Herr II, B. ., Oskotsky, B. ., Rizk-Jackson, A. ., Rankin, K. ., Sanders, S. ., Bove, R. ., Rose, P. ., Israni, S. ., & Huang, S. . (2022). A Biomedical Open Knowledge Network Harnesses the Power of AI to Understand Deep Human Biology. AI Magazine, 43(1), 46-58. https://doi.org/10.1002/aaai.12037

Issue

Vol. 43 No. 1: Spring 2022

Section

Special Topic Articles

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