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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 (88th percentile)

Mentioned by

twitter
25 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
63 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Professor 11 17%
Student > Master 7 11%
Other 6 10%
Student > Ph. D. Student 5 8%
Researcher 5 8%
Other 12 19%
Unknown 17 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 30%
Medicine and Dentistry 6 10%
Engineering 4 6%
Agricultural and Biological Sciences 4 6%
Computer Science 3 5%
Other 10 16%
Unknown 17 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
#1,645,320
of 18,038,980 outputs
Outputs from BMC Bioinformatics
#486
of 6,341 outputs
Outputs of similar age
#39,463
of 281,228 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 18 outputs
Altmetric has tracked 18,038,980 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 6,341 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 92% 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 281,228 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 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.