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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Structural Model of the Endogenous Human BAF Complex Informs Disease Mechanisms
|
|---|---|
| Published in |
Cell, October 2020
|
| DOI | 10.1016/j.cell.2020.09.051 |
| Pubmed ID | |
| Authors |
Nazar Mashtalir, Hiroshi Suzuki, Daniel P Farrell, Akshay Sankar, Jie Luo, Martin Filipovski, Andrew R D'Avino, Roodolph St Pierre, Alfredo M Valencia, Takashi Onikubo, Robert G Roeder, Yan Han, Yuan He, Jeffrey A Ranish, Frank DiMaio, Thomas Walz, Cigall Kadoch |
X Demographics
The data shown below were collected from the profiles of 197 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 | 91 | 46% |
| United Kingdom | 7 | 4% |
| Canada | 6 | 3% |
| France | 5 | 3% |
| India | 5 | 3% |
| Spain | 4 | 2% |
| Australia | 3 | 2% |
| Ireland | 2 | 1% |
| Japan | 2 | 1% |
| Other | 19 | 10% |
| Unknown | 53 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 116 | 59% |
| Members of the public | 74 | 38% |
| Practitioners (doctors, other healthcare professionals) | 5 | 3% |
| Science communicators (journalists, bloggers, editors) | 2 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 189 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 189 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 37 | 20% |
| Student > Ph. D. Student | 33 | 17% |
| Student > Bachelor | 12 | 6% |
| Student > Doctoral Student | 11 | 6% |
| Student > Master | 11 | 6% |
| Other | 28 | 15% |
| Unknown | 57 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 82 | 43% |
| Agricultural and Biological Sciences | 17 | 9% |
| Medicine and Dentistry | 11 | 6% |
| Chemistry | 5 | 3% |
| Social Sciences | 2 | 1% |
| Other | 10 | 5% |
| Unknown | 62 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 170. 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 07 April 2024.
All research outputs
#244,895
of 25,866,425 outputs
Outputs from Cell
#1,346
of 17,302 outputs
Outputs of similar age
#7,187
of 438,555 outputs
Outputs of similar age from Cell
#69
of 169 outputs
Altmetric has tracked 25,866,425 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,302 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 59.9. This one has done particularly well, scoring higher than 92% 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 438,555 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 98% of its contemporaries.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.