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Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment

Overview of attention for article published in Genome Medicine, January 2014
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
twitter
8 tweeters

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
53 Mendeley
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Title
Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment
Published in
Genome Medicine, January 2014
DOI 10.1186/gm534
Pubmed ID
Authors

Mika Gustafsson, Måns Edström, Danuta Gawel, Colm E Nestor, Hui Wang, Huan Zhang, Fredrik Barrenäs, James Tojo, Ingrid Kockum, Tomas Olsson, Jordi Serra-Musach, Núria Bonifaci, Miguel Pujana, Jan Ernerudh, Mikael Benson

Abstract

Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, i.e. shared by several diseases.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 2%
Spain 1 2%
Sweden 1 2%
Unknown 50 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 19%
Student > Master 10 19%
Student > Ph. D. Student 8 15%
Other 4 8%
Student > Postgraduate 4 8%
Other 10 19%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 25%
Agricultural and Biological Sciences 13 25%
Medicine and Dentistry 6 11%
Engineering 4 8%
Computer Science 2 4%
Other 5 9%
Unknown 10 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 2015.
All research outputs
#2,049,101
of 21,364,317 outputs
Outputs from Genome Medicine
#473
of 1,356 outputs
Outputs of similar age
#21,665
of 201,452 outputs
Outputs of similar age from Genome Medicine
#1
of 9 outputs
Altmetric has tracked 21,364,317 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 1,356 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.8. This one has gotten more attention than average, scoring higher than 65% 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 201,452 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 89% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them