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Identification of Pathologic and Prognostic Genes in Prostate Cancer Based on Database Mining

Overview of attention for article published in Frontiers in Genetics, March 2022
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1 X user

Citations

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3 Dimensions

Readers on

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16 Mendeley
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Title
Identification of Pathologic and Prognostic Genes in Prostate Cancer Based on Database Mining
Published in
Frontiers in Genetics, March 2022
DOI 10.3389/fgene.2022.854531
Pubmed ID
Authors

Kun Liu, Yijun Chen, Pengmian Feng, Yucheng Wang, Mengdi Sun, Tao Song, Jun Tan, Chunyang Li, Songpo Liu, Qinghong Kong, Jidong Zhang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 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 > Master 6 38%
Student > Bachelor 2 13%
Unknown 8 50%
Readers by discipline Count As %
Medicine and Dentistry 3 19%
Biochemistry, Genetics and Molecular Biology 2 13%
Chemical Engineering 1 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Agricultural and Biological Sciences 1 6%
Other 1 6%
Unknown 7 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 March 2022.
All research outputs
#20,718,666
of 23,317,888 outputs
Outputs from Frontiers in Genetics
#8,906
of 12,334 outputs
Outputs of similar age
#361,377
of 440,188 outputs
Outputs of similar age from Frontiers in Genetics
#554
of 872 outputs
Altmetric has tracked 23,317,888 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,334 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 440,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 872 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.