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Advanced model systems and tools for basic and translational human immunology

Overview of attention for article published in Genome Medicine, September 2018
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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 (84th percentile)

Mentioned by

25 tweeters


51 Dimensions

Readers on

178 Mendeley
1 CiteULike
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Advanced model systems and tools for basic and translational human immunology
Published in
Genome Medicine, September 2018
DOI 10.1186/s13073-018-0584-8
Pubmed ID

Lisa E. Wagar, Robert M. DiFazio, Mark M. Davis


There are fundamental differences between humans and the animals we typically use to study the immune system. We have learned much from genetically manipulated and inbred animal models, but instances in which these findings have been successfully translated to human immunity have been rare. Embracing the genetic and environmental diversity of humans can tell us about the fundamental biology of immune cell types and the elasticity of the immune system. Although people are much more immunologically diverse than conventionally housed animal models, tools and technologies are now available that permit high-throughput analysis of human samples, including both blood and tissues, which will give us deep insights into human immunity in health and disease. As we gain a more detailed picture of the human immune system, we can build more sophisticated models to better reflect this complexity, both enabling the discovery of new immunological mechanisms and facilitating translation into the clinic.

Twitter Demographics

The data shown below were collected from the profiles of 25 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 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 178 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 20%
Researcher 33 19%
Student > Master 28 16%
Student > Bachelor 20 11%
Student > Doctoral Student 9 5%
Other 22 12%
Unknown 31 17%
Readers by discipline Count As %
Immunology and Microbiology 28 16%
Biochemistry, Genetics and Molecular Biology 26 15%
Medicine and Dentistry 22 12%
Agricultural and Biological Sciences 21 12%
Engineering 10 6%
Other 29 16%
Unknown 42 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 June 2019.
All research outputs
of 19,844,828 outputs
Outputs from Genome Medicine
of 1,295 outputs
Outputs of similar age
of 292,032 outputs
Outputs of similar age from Genome Medicine
of 1 outputs
Altmetric has tracked 19,844,828 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,295 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has gotten more attention than average, scoring higher than 65% 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 292,032 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 84% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them