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Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning

Overview of attention for article published in BMC Bioinformatics, May 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
9 tweeters
facebook
1 Facebook page
reddit
1 Redditor

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
45 Mendeley
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Title
Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2853-y
Pubmed ID
Authors

Hiroki Konishi, Daisuke Komura, Hiroto Katoh, Shinichiro Atsumi, Hirotomo Koda, Asami Yamamoto, Yasuyuki Seto, Masashi Fukayama, Rui Yamaguchi, Seiya Imoto, Shumpei Ishikawa

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 18%
Researcher 8 18%
Student > Bachelor 6 13%
Student > Master 4 9%
Other 3 7%
Other 6 13%
Unknown 10 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 20%
Immunology and Microbiology 6 13%
Agricultural and Biological Sciences 5 11%
Medicine and Dentistry 5 11%
Computer Science 3 7%
Other 5 11%
Unknown 12 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 July 2019.
All research outputs
#4,650,620
of 16,994,048 outputs
Outputs from BMC Bioinformatics
#1,937
of 6,052 outputs
Outputs of similar age
#91,364
of 272,483 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 45 outputs
Altmetric has tracked 16,994,048 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 6,052 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 67% 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 272,483 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.