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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment
|
|---|---|
| Published in |
Genome Medicine, February 2014
|
| DOI | 10.1186/gm534 |
| Pubmed ID | |
| Authors |
Mika Gustafsson, Måns Edström, Danuta Gawel, Colm E Nestor, Hui Wang, Huan Zhang, Fredrik Barrenäs, James Tojo, Ingrid Kockum, Tomas Olsson, Jordi Serra-Musach, Núria Bonifaci, Miguel Angel Pujana, Jan Ernerudh, Mikael Benson |
| Abstract |
Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, i.e. shared by several diseases. |
X Demographics
The data shown below were collected from the profiles of 8 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 Kingdom | 3 | 38% |
| Korea, Republic of | 1 | 13% |
| France | 1 | 13% |
| United States | 1 | 13% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 63% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
| Members of the public | 1 | 13% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | 2% |
| Spain | 1 | 2% |
| Sweden | 1 | 2% |
| Unknown | 52 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 20% |
| Researcher | 9 | 16% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Postgraduate | 4 | 7% |
| Other | 4 | 7% |
| Other | 11 | 20% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 24% |
| Agricultural and Biological Sciences | 13 | 24% |
| Medicine and Dentistry | 7 | 13% |
| Engineering | 4 | 7% |
| Computer Science | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 11 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 30 November 2015.
All research outputs
#2,562,393
of 25,374,647 outputs
Outputs from Genome Medicine
#580
of 1,585 outputs
Outputs of similar age
#25,161
of 235,086 outputs
Outputs of similar age from Genome Medicine
#8
of 23 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. 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 235,086 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 89% of its contemporaries.
We're also able to compare this research output to 23 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 65% of its contemporaries.