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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
|
|---|---|
| Published in |
Nature Genetics, May 2016
|
| DOI | 10.1038/ng.3572 |
| Pubmed ID | |
| Authors |
Buhm Han, Jennie G Pouget, Kamil Slowikowski, Eli Stahl, Cue Hyunkyu Lee, Dorothee Diogo, Xinli Hu, Yu Rang Park, Eunji Kim, Peter K Gregersen, Solbritt Rantapää Dahlqvist, Jane Worthington, Javier Martin, Steve Eyre, Lars Klareskog, Tom Huizinga, Wei-Min Chen, Suna Onengut-Gumuscu, Stephen S Rich, Naomi R Wray, Soumya Raychaudhuri |
X Demographics
The data shown below were collected from the profiles of 57 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 | 20 | 35% |
| United Kingdom | 5 | 9% |
| Australia | 2 | 4% |
| Spain | 2 | 4% |
| Qatar | 1 | 2% |
| Denmark | 1 | 2% |
| France | 1 | 2% |
| Germany | 1 | 2% |
| Netherlands | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 23 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 30 | 53% |
| Scientists | 27 | 47% |
Mendeley readers
The data shown below were compiled from readership statistics for 215 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| Germany | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Argentina | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Luxembourg | 1 | <1% |
| Unknown | 206 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 58 | 27% |
| Researcher | 56 | 26% |
| Student > Master | 17 | 8% |
| Professor > Associate Professor | 13 | 6% |
| Student > Bachelor | 12 | 6% |
| Other | 33 | 15% |
| Unknown | 26 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 50 | 23% |
| Agricultural and Biological Sciences | 48 | 22% |
| Medicine and Dentistry | 32 | 15% |
| Neuroscience | 12 | 6% |
| Computer Science | 11 | 5% |
| Other | 23 | 11% |
| Unknown | 39 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 29 November 2022.
All research outputs
#1,360,569
of 26,017,215 outputs
Outputs from Nature Genetics
#2,079
of 7,639 outputs
Outputs of similar age
#23,809
of 343,490 outputs
Outputs of similar age from Nature Genetics
#35
of 60 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 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,639 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.7. This one has gotten more attention than average, scoring higher than 72% 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 343,490 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 60 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.