↓ Skip to main content

scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously

Overview of attention for article published in Genome Biology, June 2022
Altmetric Badge

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

Mentioned by

news
1 news outlet
twitter
66 X users

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
47 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
Published in
Genome Biology, June 2022
DOI 10.1186/s13059-022-02706-x
Pubmed ID
Authors

Ziqi Zhang, Chengkai Yang, Xiuwei Zhang

X Demographics

X Demographics

The data shown below were collected from the profiles of 66 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 36%
Researcher 7 15%
Student > Master 3 6%
Professor 2 4%
Other 1 2%
Other 2 4%
Unknown 15 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 23%
Computer Science 6 13%
Agricultural and Biological Sciences 4 9%
Immunology and Microbiology 2 4%
Medicine and Dentistry 2 4%
Other 5 11%
Unknown 17 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. 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 31 July 2022.
All research outputs
#917,938
of 25,392,582 outputs
Outputs from Genome Biology
#638
of 4,470 outputs
Outputs of similar age
#21,706
of 443,463 outputs
Outputs of similar age from Genome Biology
#11
of 58 outputs
Altmetric has tracked 25,392,582 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 85% 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 443,463 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 58 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.