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Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma

Overview of attention for article published in Frontiers in Pharmacology, March 2024
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Title
Development of a prognostic model based on different disulfidptosis related genes typing for kidney renal clear cell carcinoma
Published in
Frontiers in Pharmacology, March 2024
DOI 10.3389/fphar.2024.1343819
Pubmed ID
Authors

Yuanyuan Feng, Wenkai Wang, Shasha Jiang, Yongming Liu, Yan Wang, Xiangyang Zhan, Huirong Zhu, Guoqing Du

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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 100%
Readers by discipline Count As %
Engineering 1 100%
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 13 March 2024.
All research outputs
#22,851,193
of 25,478,886 outputs
Outputs from Frontiers in Pharmacology
#12,448
of 19,836 outputs
Outputs of similar age
#124,914
of 156,884 outputs
Outputs of similar age from Frontiers in Pharmacology
#108
of 370 outputs
Altmetric has tracked 25,478,886 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 19,836 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. 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 156,884 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 370 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.