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Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data

Overview of attention for article published in Genome Biology, February 2020
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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 (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
88 X users

Citations

dimensions_citation
222 Dimensions

Readers on

mendeley
348 Mendeley
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Title
Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data
Published in
Genome Biology, February 2020
DOI 10.1186/s13059-020-1949-z
Pubmed ID
Authors

Christian H. Holland, Jovan Tanevski, Javier Perales-Patón, Jan Gleixner, Manu P. Kumar, Elisabetta Mereu, Brian A. Joughin, Oliver Stegle, Douglas A. Lauffenburger, Holger Heyn, Bence Szalai, Julio Saez-Rodriguez

X Demographics

X Demographics

The data shown below were collected from the profiles of 88 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 348 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 348 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 75 22%
Researcher 66 19%
Student > Master 28 8%
Student > Bachelor 25 7%
Student > Postgraduate 16 5%
Other 40 11%
Unknown 98 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 106 30%
Agricultural and Biological Sciences 48 14%
Medicine and Dentistry 17 5%
Engineering 14 4%
Immunology and Microbiology 13 4%
Other 42 12%
Unknown 108 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 46. 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 09 December 2021.
All research outputs
#903,709
of 25,401,381 outputs
Outputs from Genome Biology
#617
of 4,470 outputs
Outputs of similar age
#23,821
of 476,907 outputs
Outputs of similar age from Genome Biology
#19
of 77 outputs
Altmetric has tracked 25,401,381 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 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 well, scoring higher than 86% 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 476,907 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 95% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.