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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MSstatsTMT: Statistical Detection of Differentially Abundant Proteins in Experiments with Isobaric Labeling and Multiple Mixtures
|
|---|---|
| Published in |
Molecular and Cellular Proteomics, July 2020
|
| DOI | 10.1074/mcp.ra120.002105 |
| Pubmed ID | |
| Authors |
Ting Huang, Meena Choi, Manuel Tzouros, Sabrina Golling, Nikhil Janak Pandya, Balazs Banfai, Tom Dunkley, Olga Vitek |
X Demographics
The data shown below were collected from the profiles of 57 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 22 | 39% |
| Canada | 4 | 7% |
| Italy | 2 | 4% |
| India | 2 | 4% |
| Germany | 2 | 4% |
| Sweden | 2 | 4% |
| Australia | 2 | 4% |
| Panama | 1 | 2% |
| Switzerland | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 15 | 26% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 27 | 47% |
| Members of the public | 27 | 47% |
| Practitioners (doctors, other healthcare professionals) | 2 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 119 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 32 | 27% |
| Student > Ph. D. Student | 22 | 18% |
| Student > Master | 7 | 6% |
| Professor > Associate Professor | 6 | 5% |
| Student > Bachelor | 5 | 4% |
| Other | 16 | 13% |
| Unknown | 31 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 37 | 31% |
| Agricultural and Biological Sciences | 15 | 13% |
| Chemistry | 8 | 7% |
| Neuroscience | 6 | 5% |
| Unspecified | 3 | 3% |
| Other | 20 | 17% |
| Unknown | 30 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 35. 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 24 November 2021.
All research outputs
#1,155,650
of 25,443,857 outputs
Outputs from Molecular and Cellular Proteomics
#88
of 3,224 outputs
Outputs of similar age
#32,441
of 413,929 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#4
of 35 outputs
Altmetric has tracked 25,443,857 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 3,224 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 97% 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 413,929 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 92% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.