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A transcriptome-wide association study of Alzheimer’s disease using prediction models of relevant tissues identifies novel candidate susceptibility genes

Overview of attention for article published in Genome Medicine, September 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
33 Mendeley
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Title
A transcriptome-wide association study of Alzheimer’s disease using prediction models of relevant tissues identifies novel candidate susceptibility genes
Published in
Genome Medicine, September 2021
DOI 10.1186/s13073-021-00959-y
Pubmed ID
Authors

Yanfa Sun, Jingjing Zhu, Dan Zhou, Saranya Canchi, Chong Wu, Nancy J. Cox, Robert A. Rissman, Eric R. Gamazon, Lang Wu

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Unspecified 2 6%
Student > Bachelor 2 6%
Professor 2 6%
Student > Doctoral Student 1 3%
Other 2 6%
Unknown 19 58%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 12%
Unspecified 2 6%
Engineering 2 6%
Computer Science 2 6%
Mathematics 1 3%
Other 4 12%
Unknown 18 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 12 November 2021.
All research outputs
#3,152,684
of 23,310,485 outputs
Outputs from Genome Medicine
#694
of 1,456 outputs
Outputs of similar age
#72,746
of 429,594 outputs
Outputs of similar age from Genome Medicine
#16
of 45 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,456 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one has gotten more attention than average, scoring higher than 52% 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 429,594 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.