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GenePy - a score for estimating gene pathogenicity in individuals using next-generation sequencing data

Overview of attention for article published in BMC Bioinformatics, May 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
66 Mendeley
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Title
GenePy - a score for estimating gene pathogenicity in individuals using next-generation sequencing data
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2877-3
Pubmed ID
Authors

E. Mossotto, J. J. Ashton, L. O’Gorman, R. J. Pengelly, R. M. Beattie, B. D. MacArthur, S. Ennis

Twitter Demographics

The data shown below were collected from the profiles of 10 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 18%
Researcher 12 18%
Student > Ph. D. Student 12 18%
Student > Bachelor 8 12%
Student > Postgraduate 3 5%
Other 6 9%
Unknown 13 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 29%
Medicine and Dentistry 11 17%
Computer Science 9 14%
Agricultural and Biological Sciences 6 9%
Engineering 2 3%
Other 5 8%
Unknown 14 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 May 2019.
All research outputs
#4,925,006
of 16,534,657 outputs
Outputs from BMC Bioinformatics
#2,100
of 5,960 outputs
Outputs of similar age
#98,800
of 269,025 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 46 outputs
Altmetric has tracked 16,534,657 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 5,960 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 63% 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 269,025 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.