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QueryOR: a comprehensive web platform for genetic variant analysis and prioritization

Overview of attention for article published in BMC Bioinformatics, April 2017
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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 (89th percentile)

Mentioned by

twitter
14 X users
patent
5 patents

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
52 Mendeley
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Title
QueryOR: a comprehensive web platform for genetic variant analysis and prioritization
Published in
BMC Bioinformatics, April 2017
DOI 10.1186/s12859-017-1654-4
Pubmed ID
Authors

Loris Bertoldi, Claudio Forcato, Nicola Vitulo, Giovanni Birolo, Fabio De Pascale, Erika Feltrin, Riccardo Schiavon, Franca Anglani, Susanna Negrisolo, Alessandra Zanetti, Francesca D’Avanzo, Rosella Tomanin, Georgine Faulkner, Alessandro Vezzi, Giorgio Valle

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 51 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 35%
Other 5 10%
Student > Bachelor 4 8%
Student > Ph. D. Student 4 8%
Student > Master 4 8%
Other 8 15%
Unknown 9 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 33%
Agricultural and Biological Sciences 9 17%
Computer Science 9 17%
Medicine and Dentistry 3 6%
Mathematics 1 2%
Other 2 4%
Unknown 11 21%
Attention Score in Context

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 27 February 2024.
All research outputs
#2,610,924
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#667
of 7,793 outputs
Outputs of similar age
#46,431
of 328,416 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 128 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. 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 328,416 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 128 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.