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Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis

Overview of attention for article published in Genome Biology (Online Edition), December 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

twitter
76 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
122 Mendeley
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Title
Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis
Published in
Genome Biology (Online Edition), December 2019
DOI 10.1186/s13059-019-1898-6
Pubmed ID
Authors

Shiquan Sun, Jiaqiang Zhu, Ying Ma, Xiang Zhou

Twitter Demographics

The data shown below were collected from the profiles of 76 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 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 122 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 20%
Student > Ph. D. Student 23 19%
Student > Master 14 11%
Student > Bachelor 13 11%
Student > Doctoral Student 5 4%
Other 16 13%
Unknown 27 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 45 37%
Agricultural and Biological Sciences 13 11%
Computer Science 13 11%
Medicine and Dentistry 7 6%
Neuroscience 3 2%
Other 10 8%
Unknown 31 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 39. 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 19 October 2021.
All research outputs
#715,600
of 19,191,444 outputs
Outputs from Genome Biology (Online Edition)
#607
of 3,809 outputs
Outputs of similar age
#24,192
of 412,639 outputs
Outputs of similar age from Genome Biology (Online Edition)
#83
of 289 outputs
Altmetric has tracked 19,191,444 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,809 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.9. This one has done well, scoring higher than 84% 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 412,639 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 94% of its contemporaries.
We're also able to compare this research output to 289 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.