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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis*
|
|---|---|
| Published in |
Molecular and Cellular Proteomics, March 2020
|
| DOI | 10.1074/mcp.tir119.001646 |
| Pubmed ID | |
| Authors |
Yafeng Zhu, Lukas M. Orre, Yan Zhou Tran, Georgios Mermelekas, Henrik J. Johansson, Alina Malyutina, Simon Anders, Janne Lehtiö |
X Demographics
The data shown below were collected from the profiles of 36 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 | 10 | 28% |
| Sweden | 5 | 14% |
| United Kingdom | 2 | 6% |
| Norway | 2 | 6% |
| India | 2 | 6% |
| China | 1 | 3% |
| Netherlands | 1 | 3% |
| Czechia | 1 | 3% |
| Unknown | 12 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 19 | 53% |
| Scientists | 16 | 44% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 220 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 58 | 26% |
| Researcher | 39 | 18% |
| Student > Master | 25 | 11% |
| Student > Bachelor | 14 | 6% |
| Student > Postgraduate | 9 | 4% |
| Other | 22 | 10% |
| Unknown | 53 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 75 | 34% |
| Agricultural and Biological Sciences | 38 | 17% |
| Chemistry | 9 | 4% |
| Medicine and Dentistry | 8 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 2% |
| Other | 22 | 10% |
| Unknown | 63 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 37. 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 09 August 2023.
All research outputs
#1,113,547
of 26,017,215 outputs
Outputs from Molecular and Cellular Proteomics
#81
of 3,275 outputs
Outputs of similar age
#29,144
of 395,311 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#5
of 46 outputs
Altmetric has tracked 26,017,215 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 3,275 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. 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 395,311 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 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.