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X Demographics
Mendeley readers
Attention Score in Context
| Title |
pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens
|
|---|---|
| Published in |
Genome Medicine, January 2016
|
| DOI | 10.1186/s13073-016-0264-5 |
| Pubmed ID | |
| Authors |
Jasreet Hundal, Beatriz M. Carreno, Allegra A. Petti, Gerald P. Linette, Obi L. Griffith, Elaine R. Mardis, Malachi Griffith |
X Demographics
The data shown below were collected from the profiles of 33 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 | 16 | 48% |
| United Kingdom | 4 | 12% |
| Germany | 1 | 3% |
| India | 1 | 3% |
| Canada | 1 | 3% |
| France | 1 | 3% |
| Austria | 1 | 3% |
| Unknown | 8 | 24% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 21 | 64% |
| Members of the public | 11 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 468 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 1% |
| Korea, Republic of | 1 | <1% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| Germany | 1 | <1% |
| Belgium | 1 | <1% |
| Taiwan | 1 | <1% |
| Japan | 1 | <1% |
| China | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 455 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 113 | 24% |
| Student > Ph. D. Student | 90 | 19% |
| Student > Master | 45 | 10% |
| Student > Bachelor | 30 | 6% |
| Other | 29 | 6% |
| Other | 69 | 15% |
| Unknown | 92 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 120 | 26% |
| Agricultural and Biological Sciences | 86 | 18% |
| Immunology and Microbiology | 49 | 10% |
| Medicine and Dentistry | 46 | 10% |
| Computer Science | 29 | 6% |
| Other | 36 | 8% |
| Unknown | 102 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 18 September 2021.
All research outputs
#1,017,273
of 25,837,817 outputs
Outputs from Genome Medicine
#194
of 1,611 outputs
Outputs of similar age
#17,988
of 409,501 outputs
Outputs of similar age from Genome Medicine
#6
of 33 outputs
Altmetric has tracked 25,837,817 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 1,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has done well, scoring higher than 87% 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 409,501 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 33 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.