| Title |
Nanowell-mediated multidimensional separations combining nanoLC with SLIM IM-MS for rapid, high-peak-capacity proteomic analyses
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, November 2018
|
| DOI | 10.1007/s00216-018-1452-5 |
| Pubmed ID | |
| Authors |
Maowei Dou, Christopher D. Chouinard, Ying Zhu, Gabe Nagy, Andrey V. Liyu, Yehia M. Ibrahim, Richard D. Smith, Ryan T. Kelly |
X Demographics
The data shown below were collected from the profiles of 16 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 | 8 | 50% |
| United Kingdom | 1 | 6% |
| Unknown | 7 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 63% |
| Scientists | 5 | 31% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 11% |
| Other | 3 | 11% |
| Student > Doctoral Student | 2 | 7% |
| Researcher | 2 | 7% |
| Professor > Associate Professor | 2 | 7% |
| Other | 5 | 19% |
| Unknown | 10 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 10 | 37% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Unspecified | 1 | 4% |
| Environmental Science | 1 | 4% |
| Neuroscience | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 10 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 08 September 2019.
All research outputs
#4,315,013
of 25,622,179 outputs
Outputs from Analytical & Bioanalytical Chemistry
#641
of 9,692 outputs
Outputs of similar age
#81,225
of 365,843 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#11
of 154 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,692 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 93% 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 365,843 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 154 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 93% of its contemporaries.