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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila
|
|---|---|
| Published in |
Genome Biology, November 2021
|
| DOI | 10.1186/s13059-021-02532-7 |
| Pubmed ID | |
| Authors |
Jareth C. Wolfe, Liudmila A. Mikheeva, Hani Hagras, Nicolae Radu Zabet |
X Demographics
The data shown below were collected from the profiles of 61 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 | 20 | 33% |
| United States | 8 | 13% |
| Germany | 3 | 5% |
| Sweden | 2 | 3% |
| Hong Kong | 1 | 2% |
| Poland | 1 | 2% |
| India | 1 | 2% |
| South Africa | 1 | 2% |
| Greece | 1 | 2% |
| Other | 6 | 10% |
| Unknown | 17 | 28% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 30 | 49% |
| Scientists | 29 | 48% |
| Science communicators (journalists, bloggers, editors) | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 19% |
| Student > Master | 3 | 8% |
| Researcher | 2 | 5% |
| Lecturer | 1 | 3% |
| Professor | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 20 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 16% |
| Agricultural and Biological Sciences | 4 | 11% |
| Mathematics | 1 | 3% |
| Business, Management and Accounting | 1 | 3% |
| Chemical Engineering | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 20 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 32. 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 27 January 2023.
All research outputs
#1,283,766
of 25,832,559 outputs
Outputs from Genome Biology
#957
of 4,522 outputs
Outputs of similar age
#29,577
of 445,858 outputs
Outputs of similar age from Genome Biology
#21
of 72 outputs
Altmetric has tracked 25,832,559 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,522 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 well, scoring higher than 78% 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 445,858 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 93% of its contemporaries.
We're also able to compare this research output to 72 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 70% of its contemporaries.