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X Demographics
Mendeley readers
Attention Score in Context
| Title |
AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants
|
|---|---|
| Published in |
Genome Biology, October 2020
|
| DOI | 10.1186/s13059-020-02161-6 |
| Pubmed ID | |
| Authors |
Yadollah Shahryary, Aikaterini Symeonidi, Rashmi R. Hazarika, Johanna Denkena, Talha Mubeen, Brigitte Hofmeister, Thomas van Gurp, Maria Colomé-Tatché, Koen J.F. Verhoeven, Gerald Tuskan, Robert J. Schmitz, Frank Johannes |
X Demographics
The data shown below were collected from the profiles of 11 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 | 5 | 45% |
| China | 1 | 9% |
| Indonesia | 1 | 9% |
| United States | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 2 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 55% |
| Members of the public | 4 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 21% |
| Researcher | 7 | 21% |
| Student > Master | 3 | 9% |
| Student > Bachelor | 3 | 9% |
| Professor > Associate Professor | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 9 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 55% |
| Computer Science | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Chemical Engineering | 1 | 3% |
| Physics and Astronomy | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 63. 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 March 2021.
All research outputs
#679,790
of 25,387,668 outputs
Outputs from Genome Biology
#431
of 4,470 outputs
Outputs of similar age
#19,567
of 434,595 outputs
Outputs of similar age from Genome Biology
#15
of 70 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 90% 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 434,595 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 95% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.