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Mendeley readers
Attention Score in Context
| Title |
A theoretical model of the West Nile Virus survival data
|
|---|---|
| Published in |
BMC Immunology, June 2017
|
| DOI | 10.1186/s12865-017-0206-z |
| Pubmed ID | |
| Authors |
James K. Peterson, Alison M. Kesson, Nicholas J. C. King |
| Abstract |
In this work, we develop a theoretical model that explains the survival data in West Nile Virus infection. We build a model based on three cell populations in an infected host; the collateral damage cells, the infected dividing cell, and the infected non-dividing cells. T cell-mediated lysis of each of these populations is dependent on the level of MHC-1 upregulation, which is different in the two infected cell populations, interferon-gamma and free virus levels. The model allows us to plot a measure of host health versus time for a range of initial viral doses and from that infer the dependence of minimal health versus viral dose. This inferred functional relationship between the minimal host health and viral dose is very similar to the data that has been collected for WNV survival curves under experimental conditions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 2 | 25% |
| Researcher | 2 | 25% |
| Student > Bachelor | 1 | 13% |
| Other | 1 | 13% |
| Student > Doctoral Student | 1 | 13% |
| Other | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 2 | 25% |
| Immunology and Microbiology | 2 | 25% |
| Computer Science | 1 | 13% |
| Veterinary Science and Veterinary Medicine | 1 | 13% |
| Economics, Econometrics and Finance | 1 | 13% |
| Other | 1 | 13% |
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 23 June 2017.
All research outputs
#18,556,449
of 22,982,639 outputs
Outputs from BMC Immunology
#427
of 589 outputs
Outputs of similar age
#242,024
of 316,843 outputs
Outputs of similar age from BMC Immunology
#15
of 18 outputs
Altmetric has tracked 22,982,639 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 589 research outputs from this source. They receive a mean Attention Score of 3.7. 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 316,843 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.