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Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis

Overview of attention for article published in PLOS Medicine, September 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Citations

dimensions_citation
390 Dimensions

Readers on

mendeley
420 Mendeley
citeulike
1 CiteULike
Title
Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis
Published in
PLOS Medicine, September 2018
DOI 10.1371/journal.pmed.1002654
Pubmed ID
Authors

Miriam S. Udler, Jaegil Kim, Marcin von Grotthuss, Sílvia Bonàs-Guarch, Joanne B. Cole, Joshua Chiou, Christopher D. Anderson on behalf of METASTROKE and the ISGC, Michael Boehnke, Markku Laakso, Gil Atzmon, Benjamin Glaser, Josep M. Mercader, Kyle Gaulton, Jason Flannick, Gad Getz, Jose C. Florez

X Demographics

X Demographics

The data shown below were collected from the profiles of 105 X users 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 420 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 420 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 68 16%
Student > Ph. D. Student 66 16%
Student > Master 37 9%
Student > Bachelor 36 9%
Other 22 5%
Other 67 16%
Unknown 124 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 93 22%
Medicine and Dentistry 81 19%
Agricultural and Biological Sciences 27 6%
Computer Science 11 3%
Engineering 11 3%
Other 45 11%
Unknown 152 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 236. 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 30 November 2023.
All research outputs
#163,253
of 25,732,188 outputs
Outputs from PLOS Medicine
#340
of 5,232 outputs
Outputs of similar age
#3,209
of 352,696 outputs
Outputs of similar age from PLOS Medicine
#9
of 52 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,232 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 77.0. This one has done particularly well, scoring higher than 93% of its peers.
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 352,696 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.