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X Demographics
Mendeley readers
Attention Score in Context
| Title |
VaccImm: simulating peptide vaccination in cancer therapy
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-127 |
| Pubmed ID | |
| Authors |
Joachim von Eichborn, Anna Lena Woelke, Filippo Castiglione, Robert Preissner |
| Abstract |
Despite progress in conventional cancer therapies, cancer is still one of the leading causes of death in industrial nations. Therefore, an urgent need of progress in fighting cancer remains. A promising alternative to conventional methods is immune therapy. This relies on the fact that low-immunogenic tumours can be eradicated if an immune response against them is induced. Peptide vaccination is carried out by injecting tumour peptides into a patient to trigger a specific immune response against the tumour in its entirety. However, peptide vaccination is a highly complicated treatment and currently many factors like the optimal number of epitopes are not known precisely. Therefore, it is necessary to evaluate how certain parameters influence the therapy. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 3% |
| Unknown | 35 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 25% |
| Student > Bachelor | 5 | 14% |
| Student > Master | 5 | 14% |
| Student > Ph. D. Student | 4 | 11% |
| Professor > Associate Professor | 4 | 11% |
| Other | 6 | 17% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 19% |
| Biochemistry, Genetics and Molecular Biology | 6 | 17% |
| Medicine and Dentistry | 6 | 17% |
| Computer Science | 3 | 8% |
| Engineering | 3 | 8% |
| Other | 4 | 11% |
| Unknown | 7 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 July 2013.
All research outputs
#15,270,134
of 22,707,247 outputs
Outputs from BMC Bioinformatics
#5,361
of 7,255 outputs
Outputs of similar age
#123,153
of 197,209 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 124 outputs
Altmetric has tracked 22,707,247 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,255 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 197,209 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 124 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.