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The intolerance to functional genetic variation of protein domains predicts the localization of pathogenic mutations within genes

Overview of attention for article published in Genome Biology, January 2016
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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)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
20 X users
patent
1 patent
f1000
1 research highlight platform

Citations

dimensions_citation
118 Dimensions

Readers on

mendeley
157 Mendeley
citeulike
4 CiteULike
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Title
The intolerance to functional genetic variation of protein domains predicts the localization of pathogenic mutations within genes
Published in
Genome Biology, January 2016
DOI 10.1186/s13059-016-0869-4
Pubmed ID
Authors

Ayal B. Gussow, Slavé Petrovski, Quanli Wang, Andrew S. Allen, David B. Goldstein

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
United Kingdom 2 1%
Sweden 1 <1%
Luxembourg 1 <1%
Unknown 149 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 22%
Student > Ph. D. Student 33 21%
Student > Master 18 11%
Student > Bachelor 14 9%
Other 9 6%
Other 20 13%
Unknown 29 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 46 29%
Agricultural and Biological Sciences 35 22%
Medicine and Dentistry 19 12%
Computer Science 11 7%
Neuroscience 7 4%
Other 9 6%
Unknown 30 19%
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 11 December 2023.
All research outputs
#2,498,068
of 26,017,215 outputs
Outputs from Genome Biology
#1,996
of 4,520 outputs
Outputs of similar age
#41,495
of 407,365 outputs
Outputs of similar age from Genome Biology
#42
of 66 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 4,520 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one has gotten more attention than average, scoring higher than 55% 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 407,365 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 66 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.