↓ Skip to main content

LC-MS/MS based metabolomics and proteomics reveal candidate biomarkers and molecular mechanism of early IgA nephropathy

Overview of attention for article published in Clinical Proteomics, December 2022
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
16 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
LC-MS/MS based metabolomics and proteomics reveal candidate biomarkers and molecular mechanism of early IgA nephropathy
Published in
Clinical Proteomics, December 2022
DOI 10.1186/s12014-022-09387-5
Pubmed ID
Authors

Di Zhang, Yaohan Li, Mingzhu Liang, Yan Liang, Jingkui Tian, Qiang He, Bingxian Yang, Juan Jin, Wei Zhu

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 19%
Student > Master 3 19%
Researcher 3 19%
Professor > Associate Professor 1 6%
Unknown 6 38%
Readers by discipline Count As %
Medicine and Dentistry 4 25%
Agricultural and Biological Sciences 2 13%
Biochemistry, Genetics and Molecular Biology 2 13%
Sports and Recreations 1 6%
Engineering 1 6%
Other 0 0%
Unknown 6 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 December 2022.
All research outputs
#15,079,584
of 23,946,786 outputs
Outputs from Clinical Proteomics
#155
of 297 outputs
Outputs of similar age
#209,331
of 439,538 outputs
Outputs of similar age from Clinical Proteomics
#7
of 9 outputs
Altmetric has tracked 23,946,786 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 297 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 42nd percentile – i.e., 42% 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 439,538 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.