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An interactive reference framework for modeling a dynamic immune system

Overview of attention for article published in Science, July 2015
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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 (92nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
19 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
80 Dimensions

Readers on

mendeley
222 Mendeley
citeulike
6 CiteULike
Title
An interactive reference framework for modeling a dynamic immune system
Published in
Science, July 2015
DOI 10.1126/science.1259425
Pubmed ID
Authors

Matthew H. Spitzer, Pier Federico Gherardini, Gabriela K. Fragiadakis, Nupur Bhattacharya, Robert T. Yuan, Andrew N. Hotson, Rachel Finck, Yaron Carmi, Eli R. Zunder, Wendy J. Fantl, Sean C. Bendall, Edgar G. Engleman, Garry P. Nolan, Spitzer, Matthew H, Gherardini, Pier Federico, Fragiadakis, Gabriela K, Bhattacharya, Nupur, Yuan, Robert T, Hotson, Andrew N, Finck, Rachel, Carmi, Yaron, Zunder, Eli R, Fantl, Wendy J, Bendall, Sean C, Engleman, Edgar G, Nolan, Garry P

Abstract

Immune cells function in an interacting hierarchy that coordinates the activities of various cell types according to genetic and environmental contexts. We developed graphical approaches to construct an extensible immune reference map from mass cytometry data of cells from different organs, incorporating landmark cell populations as flags on the map to compare cells from distinct samples. The maps recapitulated canonical cellular phenotypes and revealed reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune system structure, enabled direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology.

Twitter Demographics

The data shown below were collected from the profiles of 19 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 222 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 6%
Switzerland 4 2%
Germany 3 1%
Japan 3 1%
United Kingdom 3 1%
France 2 <1%
Netherlands 1 <1%
Denmark 1 <1%
South Africa 1 <1%
Other 9 4%
Unknown 182 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 136 61%
Student > Ph. D. Student 135 61%
Student > Master 34 15%
Other 33 15%
Student > Bachelor 21 9%
Other 94 42%
Readers by discipline Count As %
Agricultural and Biological Sciences 205 92%
Immunology and Microbiology 57 26%
Biochemistry, Genetics and Molecular Biology 55 25%
Medicine and Dentistry 52 23%
Unspecified 22 10%
Other 62 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 03 April 2017.
All research outputs
#623,162
of 11,531,620 outputs
Outputs from Science
#12,749
of 52,477 outputs
Outputs of similar age
#18,258
of 232,366 outputs
Outputs of similar age from Science
#391
of 762 outputs
Altmetric has tracked 11,531,620 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 52,477 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 33.9. This one has done well, scoring higher than 75% 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 232,366 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 762 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.