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Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks

Overview of attention for article published in iScience, April 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

twitter
2 X users
patent
1 patent

Readers on

mendeley
107 Mendeley
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Article details
Title
Imputing single-cell RNA-seq data by combining graph convolution and autoencoder neural networks
Published in
iScience, April 2021
DOI 10.1016/j.isci.2021.102393
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 107 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 18 17%
Researcher 17 16%
Student > Bachelor 11 10%
Student > Master 8 7%
Student > Doctoral Student 4 4%
Other 10 9%
Unknown 39 36%
Readers by discipline
Readers by discipline Count As %
Computer Science 27 25%
Biochemistry, Genetics and Molecular Biology 11 10%
Agricultural and Biological Sciences 5 5%
Engineering 5 5%
Mathematics 4 4%
Other 11 10%
Unknown 44 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 November 2025.
All research outputs
#11,322,103
of 34,089,221 outputs
Outputs from iScience
#4,879
of 12,195 outputs
Outputs of similar age
#182,629
of 480,979 outputs
Outputs of similar age from iScience
#164
of 338 outputs
Altmetric has tracked 34,089,221 research outputs across all sources so far. This one has received more attention than most of these and is in the 65th percentile.
So far Altmetric has tracked 12,195 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.7. This one has gotten more attention than average, scoring higher than 59% 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 480,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 338 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 51% of its contemporaries.