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DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies

Overview of attention for article published in Genome Biology, August 2020
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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
17 X users

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
66 Mendeley
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Title
DiMSum: an error model and pipeline for analyzing deep mutational scanning data and diagnosing common experimental pathologies
Published in
Genome Biology, August 2020
DOI 10.1186/s13059-020-02091-3
Pubmed ID
Authors

Andre J. Faure, Jörn M. Schmiedel, Pablo Baeza-Centurion, Ben Lehner

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 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 > Ph. D. Student 21 32%
Researcher 10 15%
Student > Master 5 8%
Student > Bachelor 5 8%
Student > Postgraduate 2 3%
Other 3 5%
Unknown 20 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 30%
Agricultural and Biological Sciences 12 18%
Computer Science 3 5%
Neuroscience 2 3%
Engineering 2 3%
Other 5 8%
Unknown 22 33%
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 12 August 2022.
All research outputs
#3,707,861
of 25,394,764 outputs
Outputs from Genome Biology
#2,529
of 4,470 outputs
Outputs of similar age
#93,445
of 427,008 outputs
Outputs of similar age from Genome Biology
#77
of 99 outputs
Altmetric has tracked 25,394,764 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 4,470 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 427,008 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 99 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.