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A roadmap towards personalized immunology

Overview of attention for article published in npj Systems Biology and Applications, February 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#23 of 367)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

news
1 news outlet
twitter
40 X users
facebook
2 Facebook pages
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
187 Mendeley
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Title
A roadmap towards personalized immunology
Published in
npj Systems Biology and Applications, February 2018
DOI 10.1038/s41540-017-0045-9
Pubmed ID
Authors

Sylvie Delhalle, Sebastian F. N. Bode, Rudi Balling, Markus Ollert, Feng Q. He

Abstract

Big data generation and computational processing will enable medicine to evolve from a "one-size-fits-all" approach to precise patient stratification and treatment. Significant achievements using "Omics" data have been made especially in personalized oncology. However, immune cells relative to tumor cells show a much higher degree of complexity in heterogeneity, dynamics, memory-capability, plasticity and "social" interactions. There is still a long way ahead on translating our capability to identify potentially targetable personalized biomarkers into effective personalized therapy in immune-centralized diseases. Here, we discuss the recent advances and successful applications in "Omics" data utilization and network analysis on patients' samples of clinical trials and studies, as well as the major challenges and strategies towards personalized stratification and treatment for infectious or non-communicable inflammatory diseases such as autoimmune diseases or allergies. We provide a roadmap and highlight experimental, clinical, computational analysis, data management, ethical and regulatory issues to accelerate the implementation of personalized immunology.

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 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 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 187 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 23%
Student > Ph. D. Student 21 11%
Student > Bachelor 18 10%
Student > Doctoral Student 14 7%
Other 13 7%
Other 43 23%
Unknown 35 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 39 21%
Agricultural and Biological Sciences 20 11%
Medicine and Dentistry 20 11%
Immunology and Microbiology 18 10%
Unspecified 10 5%
Other 32 17%
Unknown 48 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. 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 30 November 2023.
All research outputs
#1,132,819
of 25,450,869 outputs
Outputs from npj Systems Biology and Applications
#23
of 367 outputs
Outputs of similar age
#26,661
of 446,551 outputs
Outputs of similar age from npj Systems Biology and Applications
#3
of 11 outputs
Altmetric has tracked 25,450,869 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 367 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 94% 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 446,551 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 94% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.