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

Publication ,  Journal Article
Ong, E; Wang, LL; Schaub, J; O'Toole, JF; Steck, B; Rosenberg, AZ; Dowd, F; Hansen, J; Barisoni, L; Jain, S; de Boer, IH; Valerius, MT; He, Y ...
Published in: Nat Rev Nephrol
November 2020

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

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Published In

Nat Rev Nephrol

DOI

EISSN

1759-507X

Publication Date

November 2020

Volume

16

Issue

11

Start / End Page

686 / 696

Location

England

Related Subject Headings

  • Urology & Nephrology
  • Precision Medicine
  • Phenotype
  • Kidney Diseases
  • Humans
  • Biological Ontologies
  • Big Data
  • Atlases as Topic
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Ong, E., Wang, L. L., Schaub, J., O’Toole, J. F., Steck, B., Rosenberg, A. Z., … Kidney Precision Medicine Project. (2020). Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nat Rev Nephrol, 16(11), 686–696. https://doi.org/10.1038/s41581-020-00335-w
Ong, Edison, Lucy L. Wang, Jennifer Schaub, John F. O’Toole, Becky Steck, Avi Z. Rosenberg, Frederick Dowd, et al. “Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.Nat Rev Nephrol 16, no. 11 (November 2020): 686–96. https://doi.org/10.1038/s41581-020-00335-w.
Ong E, Wang LL, Schaub J, O’Toole JF, Steck B, Rosenberg AZ, et al. Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nat Rev Nephrol. 2020 Nov;16(11):686–96.
Ong, Edison, et al. “Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.Nat Rev Nephrol, vol. 16, no. 11, Nov. 2020, pp. 686–96. Pubmed, doi:10.1038/s41581-020-00335-w.
Ong E, Wang LL, Schaub J, O’Toole JF, Steck B, Rosenberg AZ, Dowd F, Hansen J, Barisoni L, Jain S, de Boer IH, Valerius MT, Waikar SS, Park C, Crawford DC, Alexandrov T, Anderton CR, Stoeckert C, Weng C, Diehl AD, Mungall CJ, Haendel M, Robinson PN, Himmelfarb J, Iyengar R, Kretzler M, Mooney S, He Y, Kidney Precision Medicine Project. Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nat Rev Nephrol. 2020 Nov;16(11):686–696.

Published In

Nat Rev Nephrol

DOI

EISSN

1759-507X

Publication Date

November 2020

Volume

16

Issue

11

Start / End Page

686 / 696

Location

England

Related Subject Headings

  • Urology & Nephrology
  • Precision Medicine
  • Phenotype
  • Kidney Diseases
  • Humans
  • Biological Ontologies
  • Big Data
  • Atlases as Topic
  • 3202 Clinical sciences
  • 1103 Clinical Sciences