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scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks

Overview of attention for article published in Genome Medicine, May 2021
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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 (85th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

news
1 news outlet
twitter
8 X users

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
50 Mendeley
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Title
scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks
Published in
Genome Medicine, May 2021
DOI 10.1186/s13073-021-00908-9
Pubmed ID
Authors

Ting Jin, Peter Rehani, Mufang Ying, Jiawei Huang, Shuang Liu, Panagiotis Roussos, Daifeng Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 16%
Student > Master 5 10%
Researcher 5 10%
Student > Doctoral Student 3 6%
Student > Bachelor 3 6%
Other 8 16%
Unknown 18 36%
Readers by discipline Count As %
Computer Science 7 14%
Biochemistry, Genetics and Molecular Biology 5 10%
Unspecified 3 6%
Agricultural and Biological Sciences 3 6%
Medicine and Dentistry 3 6%
Other 7 14%
Unknown 22 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 07 June 2021.
All research outputs
#2,526,789
of 24,702,628 outputs
Outputs from Genome Medicine
#587
of 1,518 outputs
Outputs of similar age
#62,205
of 439,237 outputs
Outputs of similar age from Genome Medicine
#29
of 55 outputs
Altmetric has tracked 24,702,628 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,518 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has gotten more attention than average, scoring higher than 61% 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 439,237 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 85% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.