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Big science and big data in nephrology

descriptionPublicationkeyboard_double_arrow_right Article 01 Jun 2019 English Publisher:Elsevier BVJournal:Kidney International, volume 95, pages 1,326-1,337 (issn: 0085-2538, Copyright policy )
Authors: Markus M. Rinschen; Markus M. Rinschen; Rafael Kramann; Rafael Kramann; Julio Saez-Rodriguez; Julio Saez-Rodriguez; Julio Saez-Rodriguez; +1 Authors

doi: 10.1016/j.kint.2018.11.048 , 10.18154/rwth-2020-01635

pmid: 30982672

Big science and big data in nephrology

Abstract

Kidney international 95(6), 1326-1337 (2019). doi:10.1016/j.kint.2018.11.048

Published by Elsevier, New York, NY

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Keywords

Big Data, Biomedical Research, Gene Expression Profiling, EMC OR-01, Clinical Decision-Making, Computational Biology, 610, Nephrology, Humans, Kidney Diseases, Precision Medicine, Biomarkers, info:eu-repo/classification/ddc/610

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    popularity
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
68
Top 1%
Top 10%
Top 1%
Green
hybrid
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