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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Optimal vaccination schedule search using genetic algorithm over MPI technology
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2012
|
| DOI | 10.1186/1472-6947-12-129 |
| Pubmed ID | |
| Authors |
Cristiano Calonaci, Ferdinando Chiacchio, Francesco Pappalardo |
| Abstract |
Immunological strategies that achieve the prevention of tumor growth are based on the presumption that the immune system, if triggered before tumor onset, could be able to defend from specific cancers. In supporting this assertion, in the last decade active immunization approaches prevented some virus-related cancers in humans. An immunopreventive cell vaccine for the non-virus-related human breast cancer has been recently developed. This vaccine, called Triplex, targets the HER-2-neu oncogene in HER-2/neu transgenic mice and has shown to almost completely prevent HER-2/neu-driven mammary carcinogenesis when administered with an intensive and life-long schedule. |
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 | 1 | 50% |
| India | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 13% |
| Student > Master | 2 | 13% |
| Student > Ph. D. Student | 2 | 13% |
| Student > Bachelor | 1 | 7% |
| Professor | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 5 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 20% |
| Engineering | 2 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
| Economics, Econometrics and Finance | 1 | 7% |
| Nursing and Health Professions | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 5 | 33% |
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 15 November 2012.
All research outputs
#15,256,044
of 22,685,926 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,305
of 1,979 outputs
Outputs of similar age
#112,667
of 179,099 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 42 outputs
Altmetric has tracked 22,685,926 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 1,979 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 179,099 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 42 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.