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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deconvolution of bulk blood eQTL effects into immune cell subpopulations
|
|---|---|
| Published in |
BMC Bioinformatics, June 2020
|
| DOI | 10.1186/s12859-020-03576-5 |
| Pubmed ID | |
| Authors |
Raúl Aguirre-Gamboa, Niek de Klein, Jennifer di Tommaso, Annique Claringbould, Monique GP van der Wijst, Dylan de Vries, Harm Brugge, Roy Oelen, Urmo Võsa, Maria M. Zorro, Xiaojin Chu, Olivier B. Bakker, Zuzanna Borek, Isis Ricaño-Ponce, Patrick Deelen, Cheng-Jiang Xu, Morris Swertz, Iris Jonkers, Sebo Withoff, Irma Joosten, Serena Sanna, Vinod Kumar, Hans J. P. M. Koenen, Leo A. B. Joosten, Mihai G. Netea, Cisca Wijmenga, Lude Franke, Yang Li |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 23% |
| Netherlands | 3 | 23% |
| Switzerland | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 5 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 69% |
| Members of the public | 4 | 31% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 89 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 22% |
| Researcher | 16 | 18% |
| Student > Bachelor | 9 | 10% |
| Student > Master | 6 | 7% |
| Student > Postgraduate | 4 | 4% |
| Other | 10 | 11% |
| Unknown | 24 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 28% |
| Agricultural and Biological Sciences | 17 | 19% |
| Computer Science | 5 | 6% |
| Medicine and Dentistry | 4 | 4% |
| Mathematics | 3 | 3% |
| Other | 11 | 12% |
| Unknown | 24 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 17 June 2020.
All research outputs
#3,423,221
of 24,061,085 outputs
Outputs from BMC Bioinformatics
#1,195
of 7,497 outputs
Outputs of similar age
#87,104
of 402,420 outputs
Outputs of similar age from BMC Bioinformatics
#25
of 139 outputs
Altmetric has tracked 24,061,085 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,497 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 84% 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 402,420 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 78% 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 done well, scoring higher than 82% of its contemporaries.