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Label-free quantitative proteomics identifies transforming growth factor β1 (TGF-β1) as an inhibitor of adipogenic transformation in OP9-DL1 cells and primary thymic stromal cells

Overview of attention for article published in Cell & Bioscience, June 2019
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Mentioned by

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1 X user

Citations

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4 Dimensions

Readers on

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9 Mendeley
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Title
Label-free quantitative proteomics identifies transforming growth factor β1 (TGF-β1) as an inhibitor of adipogenic transformation in OP9-DL1 cells and primary thymic stromal cells
Published in
Cell & Bioscience, June 2019
DOI 10.1186/s13578-019-0311-1
Pubmed ID
Authors

Jianxin Tan, Yajun Wang, Siliang Wang, Simeng Wu, Zhe Yuan, Xike Zhu

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Student > Bachelor 1 11%
Unspecified 1 11%
Other 1 11%
Researcher 1 11%
Other 0 0%
Unknown 3 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 33%
Unspecified 1 11%
Agricultural and Biological Sciences 1 11%
Sports and Recreations 1 11%
Unknown 3 33%
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 30 June 2019.
All research outputs
#20,574,182
of 23,151,189 outputs
Outputs from Cell & Bioscience
#845
of 960 outputs
Outputs of similar age
#300,415
of 353,109 outputs
Outputs of similar age from Cell & Bioscience
#25
of 25 outputs
Altmetric has tracked 23,151,189 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 960 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% 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 353,109 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.