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Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data

Overview of attention for article published in Frontiers in immunology, November 2017
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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 (91st percentile)

Mentioned by

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24 X users
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1 Wikipedia page

Citations

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89 Dimensions

Readers on

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98 Mendeley
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Title
Reproducibility and Reuse of Adaptive Immune Receptor Repertoire Data
Published in
Frontiers in immunology, November 2017
DOI 10.3389/fimmu.2017.01418
Pubmed ID
Authors

Felix Breden, Eline T. Luning Prak, Bjoern Peters, Florian Rubelt, Chaim A. Schramm, Christian E. Busse, Jason A. Vander Heiden, Scott Christley, Syed Ahmad Chan Bukhari, Adrian Thorogood, Frederick A. Matsen, Yariv Wine, Uri Laserson, David Klatzmann, Daniel C. Douek, Marie-Paule Lefranc, Andrew M. Collins, Tania Bubela, Steven H. Kleinstein, Corey T. Watson, Lindsay G. Cowell, Jamie K. Scott, Thomas B. Kepler

Abstract

High-throughput sequencing (HTS) of immunoglobulin (B-cell receptor, antibody) and T-cell receptor repertoires has increased dramatically since the technique was introduced in 2009 (1-3). This experimental approach explores the maturation of the adaptive immune system and its response to antigens, pathogens, and disease conditions in exquisite detail. It holds significant promise for diagnostic and therapy-guiding applications. New technology often spreads rapidly, sometimes more rapidly than the understanding of how to make the products of that technology reliable, reproducible, or usable by others. As complex technologies have developed, scientific communities have come together to adopt common standards, protocols, and policies for generating and sharing data sets, such as the MIAME protocols developed for microarray experiments. The Adaptive Immune Receptor Repertoire (AIRR) Community formed in 2015 to address similar issues for HTS data of immune repertoires. The purpose of this perspective is to provide an overview of the AIRR Community's founding principles and present the progress that the AIRR Community has made in developing standards of practice and data sharing protocols. Finally, and most important, we invite all interested parties to join this effort to facilitate sharing and use of these powerful data sets ([email protected]).

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 98 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 35%
Student > Ph. D. Student 13 13%
Student > Master 9 9%
Student > Bachelor 8 8%
Other 8 8%
Other 10 10%
Unknown 16 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 21%
Immunology and Microbiology 18 18%
Agricultural and Biological Sciences 14 14%
Medicine and Dentistry 5 5%
Engineering 3 3%
Other 12 12%
Unknown 25 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 20 July 2019.
All research outputs
#2,148,499
of 26,375,196 outputs
Outputs from Frontiers in immunology
#2,124
of 33,013 outputs
Outputs of similar age
#40,505
of 345,193 outputs
Outputs of similar age from Frontiers in immunology
#52
of 581 outputs
Altmetric has tracked 26,375,196 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 33,013 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 93% 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 345,193 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 581 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 91% of its contemporaries.