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scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data

Overview of attention for article published in Genome Biology (Online Edition), September 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 (90th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
23 tweeters

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
46 Mendeley
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Title
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data
Published in
Genome Biology (Online Edition), September 2019
DOI 10.1186/s13059-019-1806-0
Pubmed ID
Authors

Ruoxin Li, Gerald Quon

Twitter Demographics

The data shown below were collected from the profiles of 23 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 24%
Student > Bachelor 8 17%
Student > Master 5 11%
Researcher 3 7%
Student > Doctoral Student 3 7%
Other 6 13%
Unknown 10 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 28%
Computer Science 9 20%
Agricultural and Biological Sciences 6 13%
Physics and Astronomy 1 2%
Mathematics 1 2%
Other 3 7%
Unknown 13 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 22 November 2019.
All research outputs
#902,076
of 16,254,342 outputs
Outputs from Genome Biology (Online Edition)
#870
of 3,449 outputs
Outputs of similar age
#24,414
of 267,005 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 16,254,342 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,449 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.1. This one has gotten more attention than average, scoring higher than 74% 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 267,005 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them