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Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood

Overview of attention for article published in Bioinformatics, July 2012
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
1 blog
wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Citations

dimensions_citation
559 Dimensions

Readers on

mendeley
434 Mendeley
citeulike
1 CiteULike
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Title
Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood
Published in
Bioinformatics, July 2012
DOI 10.1093/bioinformatics/bts474
Pubmed ID
Authors

S.H. Lee, J. Yang, M.E. Goddard, P.M. Visscher, N.R. Wray

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 434 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 1%
United Kingdom 4 <1%
Australia 2 <1%
Sweden 1 <1%
Canada 1 <1%
Netherlands 1 <1%
Unknown 419 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 123 28%
Researcher 96 22%
Student > Master 39 9%
Student > Bachelor 24 6%
Professor 23 5%
Other 61 14%
Unknown 68 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 125 29%
Biochemistry, Genetics and Molecular Biology 68 16%
Medicine and Dentistry 44 10%
Psychology 20 5%
Computer Science 18 4%
Other 69 16%
Unknown 90 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 28 December 2020.
All research outputs
#2,481,119
of 26,017,215 outputs
Outputs from Bioinformatics
#1,834
of 12,966 outputs
Outputs of similar age
#15,611
of 182,944 outputs
Outputs of similar age from Bioinformatics
#26
of 167 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,966 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 85% 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 182,944 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 90% of its contemporaries.
We're also able to compare this research output to 167 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.