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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics*
|
|---|---|
| Published in |
Molecular and Cellular Proteomics, March 2020
|
| DOI | 10.1074/mcp.ra119.001857 |
| Pubmed ID | |
| Authors |
Chia-Feng Tsai, Rui Zhao, Sarah M. Williams, Ronald J. Moore, Kendall Schultz, William B. Chrisler, Ljiljana Pasa-Tolic, Karin D. Rodland, Richard D. Smith, Tujin Shi, Ying Zhu, Tao Liu |
X Demographics
The data shown below were collected from the profiles of 25 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 | 7 | 28% |
| United Kingdom | 2 | 8% |
| Germany | 2 | 8% |
| Australia | 1 | 4% |
| Japan | 1 | 4% |
| India | 1 | 4% |
| Italy | 1 | 4% |
| Unknown | 10 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 64% |
| Scientists | 7 | 28% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 106 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 24% |
| Researcher | 21 | 20% |
| Student > Master | 6 | 6% |
| Student > Doctoral Student | 5 | 5% |
| Professor > Associate Professor | 5 | 5% |
| Other | 12 | 11% |
| Unknown | 32 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 35 | 33% |
| Agricultural and Biological Sciences | 15 | 14% |
| Chemistry | 10 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 4% |
| Engineering | 3 | 3% |
| Other | 7 | 7% |
| Unknown | 32 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 34. 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 19 October 2022.
All research outputs
#1,187,248
of 25,707,225 outputs
Outputs from Molecular and Cellular Proteomics
#93
of 3,238 outputs
Outputs of similar age
#29,241
of 385,958 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#5
of 39 outputs
Altmetric has tracked 25,707,225 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 3,238 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 385,958 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 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.