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Non-negative low-rank representation based on dictionary learning for single-cell RNA-sequencing data analysis

Overview of attention for article published in BMC Genomics, December 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

blogs
1 blog

Readers on

mendeley
3 Mendeley
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Title
Non-negative low-rank representation based on dictionary learning for single-cell RNA-sequencing data analysis
Published in
BMC Genomics, December 2022
DOI 10.1186/s12864-022-09027-0
Pubmed ID
Authors

Juan Wang, Nana Zhang, Shasha Yuan, Junliang Shang, Lingyun Dai, Feng Li, Jinxing Liu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Doctoral Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Agricultural and Biological Sciences 1 33%
Unknown 1 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 28 December 2022.
All research outputs
#5,932,362
of 23,437,201 outputs
Outputs from BMC Genomics
#2,440
of 10,771 outputs
Outputs of similar age
#104,539
of 434,900 outputs
Outputs of similar age from BMC Genomics
#27
of 143 outputs
Altmetric has tracked 23,437,201 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 10,771 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 77% 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 434,900 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 75% of its contemporaries.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.