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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GRAde: a long-read sequencing approach to efficiently identifying the CYP11B1/CYP11B2 chimeric form in patients with glucocorticoid-remediable aldosteronism
|
|---|---|
| Published in |
BMC Bioinformatics, January 2022
|
| DOI | 10.1186/s12859-022-04561-w |
| Pubmed ID | |
| Authors |
Yu-Ching Wu, Chia-I Chen, Peng-Ying Chen, Chun-Hung Kuo, Yi-Hsuan Hung, Kang-Yung Peng, Vin-Cent Wu, Jyy-Jih Tsai-Wu, Chia-Lang Hsu |
X Demographics
The data shown below were collected from the profiles of 7 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 | 1 | 14% |
| India | 1 | 14% |
| Sweden | 1 | 14% |
| United Kingdom | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 25% |
| Unspecified | 1 | 13% |
| Other | 1 | 13% |
| Librarian | 1 | 13% |
| Student > Bachelor | 1 | 13% |
| Other | 1 | 13% |
| Unknown | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 63% |
| Biochemistry, Genetics and Molecular Biology | 1 | 13% |
| Unspecified | 1 | 13% |
| Unknown | 1 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 11 January 2022.
All research outputs
#7,061,479
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#2,639
of 7,418 outputs
Outputs of similar age
#156,725
of 515,112 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 139 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 63% 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 515,112 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 139 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 60% of its contemporaries.