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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer
|
|---|---|
| Published in |
Genome Biology, October 2014
|
| DOI | 10.1186/s13059-014-0480-5 |
| Pubmed ID | |
| Authors |
Yao Fu, Zhu Liu, Shaoke Lou, Jason Bedford, Xinmeng Jasmine Mu, Kevin Y Yip, Ekta Khurana, Mark Gerstein |
X Demographics
The data shown below were collected from the profiles of 12 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 | 4 | 33% |
| Canada | 2 | 17% |
| Spain | 1 | 8% |
| Australia | 1 | 8% |
| United Kingdom | 1 | 8% |
| Unknown | 3 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 10 | 83% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
| Members of the public | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 361 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 1% |
| United Kingdom | 4 | 1% |
| Germany | 3 | <1% |
| Hong Kong | 2 | <1% |
| Spain | 2 | <1% |
| Korea, Republic of | 1 | <1% |
| Sweden | 1 | <1% |
| Italy | 1 | <1% |
| Norway | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 340 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 111 | 31% |
| Researcher | 75 | 21% |
| Student > Master | 41 | 11% |
| Student > Bachelor | 19 | 5% |
| Student > Doctoral Student | 17 | 5% |
| Other | 43 | 12% |
| Unknown | 55 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 113 | 31% |
| Biochemistry, Genetics and Molecular Biology | 97 | 27% |
| Computer Science | 40 | 11% |
| Medicine and Dentistry | 17 | 5% |
| Engineering | 8 | 2% |
| Other | 26 | 7% |
| Unknown | 60 | 17% |
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 06 February 2019.
All research outputs
#6,493,896
of 26,017,215 outputs
Outputs from Genome Biology
#3,059
of 4,513 outputs
Outputs of similar age
#63,208
of 269,503 outputs
Outputs of similar age from Genome Biology
#61
of 106 outputs
Altmetric has tracked 26,017,215 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 4,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one is in the 31st percentile – i.e., 31% 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 269,503 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 75% of its contemporaries.
We're also able to compare this research output to 106 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.