A biomedical open knowledge network harnesses the power of AI to understand deep human biology-Reference-Cited by-同舟云学术

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

Published:2022-03 Issue:1 Volume:43 Page:46-58
ISSN:0738-4602
Container-title:AI Magazine
language:en
Short-container-title:AI Magazine

Author:

Baranzini Sergio E.¹²,Börner Katy³,Morris John⁴,Nelson Charlotte A.¹,Soman Karthik¹,Schleimer Erica¹,Keiser Michael⁴⁵,Musen Mark⁶,Pearce Roger⁷,Reza Tahsin⁷,Smith Brett⁸,Herr Bruce W.³,Oskotsky Boris²,Rizk‐Jackson Angela²,Rankin Katherine P.¹²,Sanders Stephan J.²⁹,Bove Riley¹²,Rose Peter W.¹⁰,Israni Sharat²,Huang Sui⁸

Affiliation:

1. Weill Institute for Neurosciences Department of Neurology University of California San Francisco San Francisco California USA

2. Bakar Institute for Computational Health Sciences University of California San Francisco San Francisco California USA

3. Department of Intelligent Systems Engineering Indiana University Bloomington Indiana USA

4. Department of Pharmaceutical Chemistry University of California San Francisco San Francisco California USA

5. Institute for Neurodegenerative Diseases University of California San Francisco San Francisco California USA

6. Department of Medicine (Biomedical Informatics) and of Biomedical Data Science Stanford University School of Medicine Stanford California USA

7. Center for Applied Scientific Computing (CASC) Lawrence Livermore National Laboratory Livermore California USA

8. Institute for Systems Biology Seattle Washington USA

9. Weill Institute for Neurosciences Department of Psychiatry and Behavioral Sciences University of California San Francisco San Francisco California USA

10. San Diego Supercomputer Center University of California San Diego La Jolla California USA

Funder

National Science Foundation

Publisher

Wiley

Subject

Artificial Intelligence

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aaai.12037

Reference26 articles.

1. Bordes A. N.Usunier A.Garcia‐Durán J.Weston andO.Yakhnenko.2013. “Translating Embeddings for Modeling Multi‐relational Data.” InProceedings Proceedings of the 26th International Conference on Neural Information Processing Systems Vol. 2 2787–95.Lake Tahoe Nevada.

2. Kleisli: a new tool for data integration in biology

3. Toward A Universal Biomedical Data Translator

4. Innovation in the pharmaceutical industry: New estimates of R&D costs

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