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VarSight: prioritizing clinically reported variants with binary classification algorithms

Overview of attention for article published in BMC Bioinformatics, October 2019
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
25 tweeters

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
89 Mendeley
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Title
VarSight: prioritizing clinically reported variants with binary classification algorithms
Published in
BMC Bioinformatics, October 2019
DOI 10.1186/s12859-019-3026-8
Pubmed ID
Authors

James M. Holt, Brandon Wilk, Camille L. Birch, Donna M. Brown, Manavalan Gajapathy, Alexander C. Moss, Nadiya Sosonkina, Melissa A. Wilk, Julie A. Anderson, Jeremy M. Harris, Jacob M. Kelly, Fariba Shaterferdosian, Angelina E. Uno-Antonison, Arthur Weborg, Elizabeth A. Worthey

Twitter Demographics

The data shown below were collected from the profiles of 25 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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 15%
Professor 11 12%
Other 10 11%
Student > Master 10 11%
Student > Ph. D. Student 8 9%
Other 15 17%
Unknown 22 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 31 35%
Medicine and Dentistry 7 8%
Computer Science 5 6%
Agricultural and Biological Sciences 5 6%
Engineering 4 4%
Other 13 15%
Unknown 24 27%

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 26 June 2020.
All research outputs
#2,092,771
of 22,487,039 outputs
Outputs from BMC Bioinformatics
#579
of 7,191 outputs
Outputs of similar age
#42,316
of 297,468 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 19 outputs
Altmetric has tracked 22,487,039 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 7,191 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 91% 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 297,468 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 85% of its contemporaries.
We're also able to compare this research output to 19 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.