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GeneYenta: A Phenotype­Based Rare Disease Case Matching Tool Based on Online Dating Algorithms for the Acceleration of Exome Interpretation

Overview of attention for article published in Human Mutation, March 2015
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
9 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
29 Mendeley
citeulike
1 CiteULike
Title
GeneYenta: A Phenotype­Based Rare Disease Case Matching Tool Based on Online Dating Algorithms for the Acceleration of Exome Interpretation
Published in
Human Mutation, March 2015
DOI 10.1002/humu.22772
Pubmed ID
Authors

Michael M. Gottlieb, David J. Arenillas, Savanie Maithripala, Zachary D. Maurer, Maja Tarailo­Graovac, Linlea Armstrong, Millan Patel, Clara van Karnebeek, Wyeth W. Wasserman

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 21%
Student > Ph. D. Student 5 17%
Researcher 4 14%
Professor 2 7%
Student > Postgraduate 2 7%
Other 3 10%
Unknown 7 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 24%
Medicine and Dentistry 5 17%
Biochemistry, Genetics and Molecular Biology 4 14%
Computer Science 3 10%
Nursing and Health Professions 1 3%
Other 1 3%
Unknown 8 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 2021.
All research outputs
#1,918,173
of 25,374,647 outputs
Outputs from Human Mutation
#70
of 2,982 outputs
Outputs of similar age
#24,399
of 278,594 outputs
Outputs of similar age from Human Mutation
#2
of 41 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,982 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 97% 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 278,594 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 91% of its contemporaries.
We're also able to compare this research output to 41 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.