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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The use of systems biology and immunological big data to guide vaccine development
|
|---|---|
| Published in |
Genome Medicine, November 2015
|
| DOI | 10.1186/s13073-015-0236-1 |
| Pubmed ID | |
| Authors |
Christoph J. Blohmke, Daniel O’Connor, Andrew J. Pollard |
| Abstract |
High-throughput technologies applied to the analysis of vaccine responses are likely to reveal the mechanisms responsible for vaccine-induced protection, aid understanding of vaccine safety and help accelerate vaccine development and clinical trials. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| Australia | 1 | 20% |
| France | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 40% |
| Members of the public | 2 | 40% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 54 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 30% |
| Student > Ph. D. Student | 11 | 20% |
| Other | 4 | 7% |
| Student > Bachelor | 3 | 5% |
| Student > Doctoral Student | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 12 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 14% |
| Biochemistry, Genetics and Molecular Biology | 7 | 13% |
| Agricultural and Biological Sciences | 7 | 13% |
| Immunology and Microbiology | 6 | 11% |
| Computer Science | 4 | 7% |
| Other | 9 | 16% |
| Unknown | 15 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 14 April 2020.
All research outputs
#13,216,332
of 22,832,057 outputs
Outputs from Genome Medicine
#1,214
of 1,442 outputs
Outputs of similar age
#129,847
of 282,783 outputs
Outputs of similar age from Genome Medicine
#28
of 31 outputs
Altmetric has tracked 22,832,057 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,442 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one is in the 14th percentile – i.e., 14% 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 282,783 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.