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Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation

Overview of attention for article published in Frontiers in immunology, February 2024
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Title
Identification of cuproptosis-related gene clusters and immune cell infiltration in major burns based on machine learning models and experimental validation
Published in
Frontiers in immunology, February 2024
DOI 10.3389/fimmu.2024.1335675
Pubmed ID
Authors

Xin Wang, Zhenfang Xiong, Wangbing Hong, Xincheng Liao, Guangping Yang, Zhengying Jiang, Lanxin Jing, Shengyu Huang, Zhonghua Fu, Feng Zhu

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 %
Unspecified 1 100%
Readers by discipline Count As %
Unspecified 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 12 February 2024.
All research outputs
#23,093,097
of 25,738,558 outputs
Outputs from Frontiers in immunology
#27,962
of 32,294 outputs
Outputs of similar age
#285,283
of 351,193 outputs
Outputs of similar age from Frontiers in immunology
#905
of 1,185 outputs
Altmetric has tracked 25,738,558 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 32,294 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. 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 351,193 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 1,185 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.