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Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

blogs
1 blog
twitter
193 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
198 Dimensions

Readers on

mendeley
446 Mendeley
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Title
Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
Published in
Genome Biology (Online Edition), December 2019
DOI 10.1186/s13059-019-1861-6
Pubmed ID
Authors

F. William Townes, Stephanie C. Hicks, Martin J. Aryee, Rafael A. Irizarry

Twitter Demographics

The data shown below were collected from the profiles of 193 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 446 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 446 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 131 29%
Researcher 72 16%
Student > Bachelor 46 10%
Student > Master 35 8%
Student > Doctoral Student 22 5%
Other 43 10%
Unknown 97 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 130 29%
Agricultural and Biological Sciences 76 17%
Computer Science 41 9%
Mathematics 19 4%
Neuroscience 14 3%
Other 51 11%
Unknown 115 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 111. 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 08 June 2022.
All research outputs
#287,424
of 21,538,985 outputs
Outputs from Genome Biology (Online Edition)
#166
of 3,984 outputs
Outputs of similar age
#8,731
of 425,598 outputs
Outputs of similar age from Genome Biology (Online Edition)
#25
of 289 outputs
Altmetric has tracked 21,538,985 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,984 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 95% 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 425,598 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 97% 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 done particularly well, scoring higher than 91% of its contemporaries.