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Understanding natural killer cell regulation by mathematical approaches

Overview of attention for article published in Frontiers in immunology, January 2012
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  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

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2 X users
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1 Wikipedia page

Citations

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10 Dimensions

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28 Mendeley
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Title
Understanding natural killer cell regulation by mathematical approaches
Published in
Frontiers in immunology, January 2012
DOI 10.3389/fimmu.2012.00359
Pubmed ID
Authors

Carsten Watzl, Michal Sternberg-Simon, Doris Urlaub, Ramit Mehr

Abstract

The activity of natural killer (NK) cells is regulated by various processes including education/licensing, priming, integration of positive and negative signals through an array of activating and inhibitory receptors, and the development of memory-like functionality. These processes are often very complex due to the large number of different receptors and signaling pathways involved. Understanding these complex mechanisms is therefore a challenge, but is critical for understanding NK cell regulation. Mathematical approaches can facilitate the analysis and understanding of complex systems. Therefore, they may be instrumental for studies in NK cell biology. Here we provide a review of the different mathematical approaches to the analysis of NK cell signal integration, activation, proliferation, and the acquisition of inhibitory receptors. These studies show how mathematical methods can aid the analysis of NK cell regulation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
Romania 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 18%
Professor 4 14%
Student > Ph. D. Student 4 14%
Student > Master 4 14%
Other 2 7%
Other 6 21%
Unknown 3 11%
Readers by discipline Count As %
Immunology and Microbiology 7 25%
Agricultural and Biological Sciences 6 21%
Biochemistry, Genetics and Molecular Biology 4 14%
Medicine and Dentistry 4 14%
Mathematics 2 7%
Other 2 7%
Unknown 3 11%
Attention Score in Context

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 07 May 2023.
All research outputs
#7,205,295
of 25,374,647 outputs
Outputs from Frontiers in immunology
#8,110
of 31,520 outputs
Outputs of similar age
#59,348
of 250,100 outputs
Outputs of similar age from Frontiers in immunology
#38
of 275 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 31,520 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has gotten more attention than average, scoring higher than 73% 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 250,100 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 75% of its contemporaries.
We're also able to compare this research output to 275 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.