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Transcriptional Control of Lineage Differentiation in Immune Cells

Overview of attention for book
Attention for Chapter 372: Transcriptional Regulatory Networks for CD4 T Cell Differentiation.
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1 X user
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80 Mendeley
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1 CiteULike
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Chapter title
Transcriptional Regulatory Networks for CD4 T Cell Differentiation.
Chapter number 372
Book title
Transcriptional Control of Lineage Differentiation in Immune Cells
Published in
Current topics in microbiology and immunology, May 2014
DOI 10.1007/82_2014_372
Pubmed ID
Book ISBNs
978-3-31-907394-1, 978-3-31-907395-8
Authors

Darah Christie, Jinfang Zhu

Abstract

CD4(+) T cells play a central role in controlling the adaptive immune response by secreting cytokines to activate target cells. Naïve CD4(+) T cells differentiate into at least four subsets, Th1Th1 , Th2Th2 , Th17Th17 , and inducible regulatory T cellsregulatory T cells , each with unique functions for pathogen elimination. The differentiation of these subsets is induced in response to cytokine stimulation, which is translated into Stat activation, followed by induction of master regulator transcription factorstranscription factors . In addition to these factors, multiple other transcription factors, both subset specific and shared, are also involved in promoting subset differentiation. This review will focus on the network of transcription factors that control CD4(+) T cell differentiation.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Greece 1 1%
Canada 1 1%
Unknown 76 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 26%
Student > Bachelor 13 16%
Researcher 13 16%
Student > Master 9 11%
Other 4 5%
Other 5 6%
Unknown 15 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 24%
Biochemistry, Genetics and Molecular Biology 17 21%
Immunology and Microbiology 16 20%
Medicine and Dentistry 7 9%
Engineering 2 3%
Other 2 3%
Unknown 17 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 October 2014.
All research outputs
#20,593,934
of 26,184,649 outputs
Outputs from Current topics in microbiology and immunology
#549
of 715 outputs
Outputs of similar age
#171,488
of 243,790 outputs
Outputs of similar age from Current topics in microbiology and immunology
#6
of 10 outputs
Altmetric has tracked 26,184,649 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 715 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 243,790 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.