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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sequence signatures extracted from proximal promoters can be used to predict distal enhancers
|
|---|---|
| Published in |
Genome Biology, December 2013
|
| DOI | 10.1186/gb-2013-14-10-r117 |
| Pubmed ID | |
| Authors |
Leila Taher, Robin P Smith, Mee J Kim, Nadav Ahituv, Ivan Ovcharenko |
| Abstract |
Gene expression is controlled by proximal promoters and distal regulatory elements such as enhancers. While the activity of some promoters can be invariant across tissues, enhancers tend to be highly tissue-specific. |
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 % |
|---|---|---|
| France | 1 | 11% |
| Spain | 1 | 11% |
| United States | 1 | 11% |
| Germany | 1 | 11% |
| United Kingdom | 1 | 11% |
| India | 1 | 11% |
| Japan | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 44% |
| Members of the public | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 5% |
| United Kingdom | 4 | 4% |
| Hong Kong | 1 | 1% |
| China | 1 | 1% |
| Italy | 1 | 1% |
| Unknown | 88 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 30% |
| Researcher | 19 | 19% |
| Student > Master | 10 | 10% |
| Professor | 7 | 7% |
| Student > Doctoral Student | 7 | 7% |
| Other | 18 | 18% |
| Unknown | 9 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 55 | 55% |
| Biochemistry, Genetics and Molecular Biology | 15 | 15% |
| Computer Science | 6 | 6% |
| Medicine and Dentistry | 5 | 5% |
| Mathematics | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 13 | 13% |
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 20 May 2020.
All research outputs
#3,526,523
of 25,373,627 outputs
Outputs from Genome Biology
#2,449
of 4,467 outputs
Outputs of similar age
#39,407
of 320,161 outputs
Outputs of similar age from Genome Biology
#55
of 97 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 320,161 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 87% of its contemporaries.
We're also able to compare this research output to 97 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.