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MMSplice: modular modeling improves the predictions of genetic variant effects on splicing

Overview of attention for article published in Genome Biology, March 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)

Mentioned by

twitter
18 X users

Citations

dimensions_citation
156 Dimensions

Readers on

mendeley
151 Mendeley
citeulike
1 CiteULike
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Title
MMSplice: modular modeling improves the predictions of genetic variant effects on splicing
Published in
Genome Biology, March 2019
DOI 10.1186/s13059-019-1653-z
Pubmed ID
Authors

Jun Cheng, Thi Yen Duong Nguyen, Kamil J. Cygan, Muhammed Hasan Çelik, William G. Fairbrother, žiga Avsec, Julien Gagneur

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 151 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 27%
Researcher 28 19%
Student > Master 13 9%
Student > Doctoral Student 9 6%
Other 8 5%
Other 20 13%
Unknown 32 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 38%
Agricultural and Biological Sciences 25 17%
Computer Science 13 9%
Physics and Astronomy 4 3%
Engineering 4 3%
Other 8 5%
Unknown 40 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 05 May 2019.
All research outputs
#3,755,762
of 25,385,509 outputs
Outputs from Genome Biology
#2,539
of 4,468 outputs
Outputs of similar age
#80,754
of 367,999 outputs
Outputs of similar age from Genome Biology
#43
of 55 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 367,999 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 78% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.