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Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

Overview of attention for article published in BioData Mining, January 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
20 tweeters

Readers on

mendeley
16 Mendeley
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Title
Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data
Published in
BioData Mining, January 2022
DOI 10.1186/s13040-021-00285-4
Pubmed ID
Authors

Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo, Isabel Nepomuceno

Twitter Demographics

The data shown below were collected from the profiles of 20 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 25%
Researcher 4 25%
Student > Bachelor 1 6%
Unspecified 1 6%
Student > Master 1 6%
Other 1 6%
Unknown 4 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Computer Science 3 19%
Unspecified 2 13%
Agricultural and Biological Sciences 1 6%
Social Sciences 1 6%
Other 1 6%
Unknown 4 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 10 January 2022.
All research outputs
#2,496,407
of 20,756,832 outputs
Outputs from BioData Mining
#64
of 297 outputs
Outputs of similar age
#71,201
of 437,184 outputs
Outputs of similar age from BioData Mining
#7
of 34 outputs
Altmetric has tracked 20,756,832 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 297 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 78% 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 437,184 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 83% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.