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Categorization of humans in biomedical research: genes, race and disease

Overview of attention for article published in Genome Biology, July 2002
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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 (95th percentile)

Mentioned by

news
4 news outlets
blogs
6 blogs
twitter
126 X users
facebook
2 Facebook pages
wikipedia
27 Wikipedia pages
googleplus
1 Google+ user
reddit
1 Redditor
video
1 YouTube creator

Citations

dimensions_citation
649 Dimensions

Readers on

mendeley
369 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
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Title
Categorization of humans in biomedical research: genes, race and disease
Published in
Genome Biology, July 2002
DOI 10.1186/gb-2002-3-7-comment2007
Pubmed ID
Authors

Neil Risch, Esteban Burchard, Elad Ziv, Hua Tang

Abstract

A debate has arisen regarding the validity of racial/ethnic categories for biomedical and genetic research. An epidemiologic perspective on the issue of human categorization in biomedical and genetic research strongly supports the continued use of self-identified race and ethnicity.

X Demographics

X Demographics

The data shown below were collected from the profiles of 126 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 369 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 3%
Brazil 4 1%
Malaysia 2 <1%
Colombia 1 <1%
Switzerland 1 <1%
Germany 1 <1%
South Africa 1 <1%
Lithuania 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 345 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 18%
Researcher 62 17%
Student > Master 43 12%
Student > Bachelor 43 12%
Professor > Associate Professor 25 7%
Other 85 23%
Unknown 45 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 87 24%
Medicine and Dentistry 56 15%
Social Sciences 53 14%
Biochemistry, Genetics and Molecular Biology 37 10%
Psychology 16 4%
Other 60 16%
Unknown 60 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 175. 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 17 April 2024.
All research outputs
#235,476
of 25,770,491 outputs
Outputs from Genome Biology
#81
of 4,516 outputs
Outputs of similar age
#148
of 48,659 outputs
Outputs of similar age from Genome Biology
#1
of 23 outputs
Altmetric has tracked 25,770,491 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 4,516 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 98% 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 48,659 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 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.