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Innovative prognostic modeling in ESCC: leveraging scRNA-seq and bulk-RNA for dendritic cell heterogeneity analysis

Overview of attention for article published in Frontiers in immunology, March 2024
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Mentioned by

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2 X users

Citations

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Title
Innovative prognostic modeling in ESCC: leveraging scRNA-seq and bulk-RNA for dendritic cell heterogeneity analysis
Published in
Frontiers in immunology, March 2024
DOI 10.3389/fimmu.2024.1352454
Pubmed ID
Authors

Mengnan Shi, Han Zhang, Linnan Ma, Xiaoting Wang, Daqiang Sun, Zhijie Feng

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
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 > Master 1 100%
Readers by discipline Count As %
Nursing and Health Professions 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 06 March 2024.
All research outputs
#21,293,063
of 26,148,761 outputs
Outputs from Frontiers in immunology
#25,523
of 32,975 outputs
Outputs of similar age
#241,010
of 349,319 outputs
Outputs of similar age from Frontiers in immunology
#685
of 1,207 outputs
Altmetric has tracked 26,148,761 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 32,975 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 14th percentile – i.e., 14% 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 349,319 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,207 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.