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deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors

Overview of attention for article published in Frontiers in Genetics, August 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
3 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
30 Mendeley
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Title
deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors
Published in
Frontiers in Genetics, August 2021
DOI 10.3389/fgene.2021.708981
Pubmed ID
Authors

Bin Zou, Tongda Zhang, Ruilong Zhou, Xiaosen Jiang, Huanming Yang, Xin Jin, Yong Bai

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 20%
Student > Bachelor 5 17%
Student > Ph. D. Student 3 10%
Student > Postgraduate 2 7%
Student > Doctoral Student 2 7%
Other 3 10%
Unknown 9 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 23%
Engineering 3 10%
Agricultural and Biological Sciences 3 10%
Environmental Science 1 3%
Veterinary Science and Veterinary Medicine 1 3%
Other 3 10%
Unknown 12 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 December 2021.
All research outputs
#3,894,177
of 22,684,168 outputs
Outputs from Frontiers in Genetics
#1,168
of 11,749 outputs
Outputs of similar age
#86,985
of 427,691 outputs
Outputs of similar age from Frontiers in Genetics
#52
of 743 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,749 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 90% 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 427,691 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 743 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 92% of its contemporaries.