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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
75 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
78 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 75 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 26%
Researcher 17 22%
Student > Master 7 9%
Student > Bachelor 7 9%
Other 3 4%
Other 10 13%
Unknown 14 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 29 37%
Agricultural and Biological Sciences 10 13%
Computer Science 9 12%
Medicine and Dentistry 5 6%
Neuroscience 2 3%
Other 6 8%
Unknown 17 22%

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 14 May 2020.
All research outputs
#544,859
of 15,488,293 outputs
Outputs from Genome Biology (Online Edition)
#500
of 3,337 outputs
Outputs of similar age
#20,710
of 355,149 outputs
Outputs of similar age from Genome Biology (Online Edition)
#83
of 290 outputs
Altmetric has tracked 15,488,293 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 3,337 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.3. 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 355,149 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 290 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.