↓ Skip to main content

Machine Learning Approaches to TCR Repertoire Analysis

Overview of attention for article published in Frontiers in immunology, July 2022
Altmetric Badge

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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

twitter
31 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
51 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Machine Learning Approaches to TCR Repertoire Analysis
Published in
Frontiers in immunology, July 2022
DOI 10.3389/fimmu.2022.858057
Pubmed ID
Authors

Yotaro Katayama, Ryo Yokota, Taishin Akiyama, Tetsuya J. Kobayashi

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 14%
Student > Ph. D. Student 7 14%
Student > Bachelor 5 10%
Other 4 8%
Professor 2 4%
Other 0 0%
Unknown 26 51%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 12%
Immunology and Microbiology 4 8%
Agricultural and Biological Sciences 3 6%
Computer Science 3 6%
Unspecified 2 4%
Other 5 10%
Unknown 28 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 28 April 2024.
All research outputs
#2,372,738
of 26,563,746 outputs
Outputs from Frontiers in immunology
#2,380
of 33,385 outputs
Outputs of similar age
#49,957
of 442,929 outputs
Outputs of similar age from Frontiers in immunology
#120
of 2,021 outputs
Altmetric has tracked 26,563,746 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 33,385 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one has done particularly well, scoring higher than 92% 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 442,929 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 88% of its contemporaries.
We're also able to compare this research output to 2,021 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.