Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project-Reference-Cited by-同舟云学术

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

Published:2020-09-16 Issue:11 Volume:16 Page:686-696
ISSN:1759-5061
Container-title:Nature Reviews Nephrology
language:en
Short-container-title:Nat Rev Nephrol

Author:

Ong Edison^ORCID,Wang Lucy L.^ORCID,Schaub Jennifer^ORCID,O’Toole John F.,Steck Becky^ORCID,Rosenberg Avi Z.,Dowd Frederick^ORCID,Hansen Jens,Barisoni Laura^ORCID,Jain Sanjay,de Boer Ian H.,Valerius M. Todd^ORCID,Waikar Sushrut S.,Park Christopher,Crawford Dana C.^ORCID,Alexandrov Theodore^ORCID,Anderton Christopher R.^ORCID,Stoeckert Christian^ORCID,Weng Chunhua,Diehl Alexander D.^ORCID,Mungall Christopher J.,Haendel Melissa,Robinson Peter N.^ORCID,Himmelfarb Jonathan^ORCID,Iyengar Ravi,Kretzler Matthias^ORCID,Mooney Sean,He Yongqun^ORCID,

Publisher

Springer Science and Business Media LLC

Subject

Nephrology

Link

https://www.nature.com/articles/s41581-020-00335-w.pdf

Reference57 articles.

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3. Stevens, P. E. & Levin, A. Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann. Intern. Med. 158, 825–830 (2013).

4. Hawrylycz, M. et al. in Springer Handbook of Bio-/Neuroinformatics. (ed. Kasabov, N.) 1111–1126 (Springer, 2014).

5. Cancer Genome Atlas Research Network. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat. Genet. 45, 1113–1120 (2013).

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