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A novel network-based approach for discovering dynamic metabolic biomarkers in cardiovascular disease

Overview of attention for article published in PLOS ONE, December 2018
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Mentioned by

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1 X user

Citations

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7 Dimensions

Readers on

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11 Mendeley
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Title
A novel network-based approach for discovering dynamic metabolic biomarkers in cardiovascular disease
Published in
PLOS ONE, December 2018
DOI 10.1371/journal.pone.0208953
Pubmed ID
Authors

Christian Baumgartner, Verena Spath-Blass, Verena Niederkofler, Katharina Bergmoser, Sonja Langthaler, Alexander Lassnig, Theresa Rienmüller, Daniela Baumgartner, Aarti Asnani, Robert E. Gerszten

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Student > Master 2 18%
Researcher 2 18%
Student > Bachelor 1 9%
Unknown 3 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 27%
Computer Science 2 18%
Physics and Astronomy 1 9%
Medicine and Dentistry 1 9%
Unknown 4 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2018.
All research outputs
#18,661,637
of 23,120,280 outputs
Outputs from PLOS ONE
#157,406
of 197,281 outputs
Outputs of similar age
#325,029
of 437,117 outputs
Outputs of similar age from PLOS ONE
#2,533
of 3,128 outputs
Altmetric has tracked 23,120,280 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 197,281 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,117 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,128 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.