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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Hydra: A mixture modeling framework for subtyping pediatric cancer cohorts using multimodal gene expression signatures
|
|---|---|
| Published in |
PLoS Computational Biology, April 2020
|
| DOI | 10.1371/journal.pcbi.1007753 |
| Pubmed ID | |
| Authors |
Jacob Pfeil, Lauren M. Sanders, Ioannis Anastopoulos, A. Geoffrey Lyle, Alana S. Weinstein, Yuanqing Xue, Andrew Blair, Holly C. Beale, Alex Lee, Stanley G. Leung, Phuong T. Dinh, Avanthi Tayi Shah, Marcus R. Breese, W. Patrick Devine, Isabel Bjork, Sofie R. Salama, E. Alejandro Sweet-Cordero, David Haussler, Olena Morozova Vaske |
X Demographics
The data shown below were collected from the profiles of 9 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 | 2 | 22% |
| Austria | 1 | 11% |
| Unknown | 6 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 56% |
| Scientists | 2 | 22% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 30% |
| Student > Ph. D. Student | 5 | 19% |
| Student > Bachelor | 4 | 15% |
| Student > Doctoral Student | 1 | 4% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 6 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 22% |
| Medicine and Dentistry | 4 | 15% |
| Agricultural and Biological Sciences | 3 | 11% |
| Social Sciences | 2 | 7% |
| Nursing and Health Professions | 1 | 4% |
| Other | 4 | 15% |
| Unknown | 7 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 21 October 2020.
All research outputs
#6,405,417
of 25,611,630 outputs
Outputs from PLoS Computational Biology
#4,349
of 9,015 outputs
Outputs of similar age
#123,469
of 401,630 outputs
Outputs of similar age from PLoS Computational Biology
#108
of 189 outputs
Altmetric has tracked 25,611,630 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 9,015 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 51% 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 401,630 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 189 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.