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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting heterogeneity in clone-specific therapeutic vulnerabilities using single-cell transcriptomic signatures
|
|---|---|
| Published in |
Genome Medicine, December 2021
|
| DOI | 10.1186/s13073-021-01000-y |
| Pubmed ID | |
| Authors |
Chayaporn Suphavilai, Shumei Chia, Ankur Sharma, Lorna Tu, Rafael Peres Da Silva, Aanchal Mongia, Ramanuj DasGupta, Niranjan Nagarajan |
X Demographics
The data shown below were collected from the profiles of 18 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 | 17% |
| United States | 2 | 11% |
| Australia | 2 | 11% |
| Germany | 1 | 6% |
| Comoros | 1 | 6% |
| Italy | 1 | 6% |
| Singapore | 1 | 6% |
| Unknown | 7 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 61% |
| Scientists | 7 | 39% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 20% |
| Researcher | 9 | 20% |
| Student > Bachelor | 4 | 9% |
| Student > Master | 2 | 5% |
| Unspecified | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 17 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 14% |
| Computer Science | 5 | 11% |
| Social Sciences | 4 | 9% |
| Medicine and Dentistry | 3 | 7% |
| Agricultural and Biological Sciences | 3 | 7% |
| Other | 6 | 14% |
| Unknown | 17 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 01 December 2023.
All research outputs
#1,856,186
of 24,911,633 outputs
Outputs from Genome Medicine
#413
of 1,535 outputs
Outputs of similar age
#44,508
of 514,777 outputs
Outputs of similar age from Genome Medicine
#7
of 27 outputs
Altmetric has tracked 24,911,633 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,535 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.1. This one has gotten more attention than average, scoring higher than 73% 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 514,777 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 91% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.