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Mendeley readers
Attention Score in Context
| Title |
Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, May 2014
|
| DOI | 10.1186/1742-4682-11-22 |
| Pubmed ID | |
| Authors |
Hiroki Ikeda, Rob J de Boer, Kei Sato, Satoru Morita, Naoko Misawa, Yoshio Koyanagi, Kazuyuki Aihara, Shingo Iwami |
| Abstract |
Mathematical modeling of virus dynamics has provided quantitative insights into viral infections such as influenza, the simian immunodeficiency virus/human immunodeficiency virus, hepatitis B, and hepatitis C. Through modeling, we can estimate the half-life of infected cells, the exponential growth rate, and the basic reproduction number (R0). To calculate R0 from virus load data, the death rate of productively infected cells is required. This can be readily estimated from treatment data collected during the chronic phase, but is difficult to determine from acute infection data. Here, we propose two new models that can reliably estimate the average life span of infected cells from acute-phase data, and apply both methods to experimental data from humanized mice infected with HIV-1. |
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 % |
|---|---|---|
| Members of the public | 1 | 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 % |
|---|---|---|
| Argentina | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 33% |
| Student > Ph. D. Student | 4 | 27% |
| Student > Master | 3 | 20% |
| Student > Bachelor | 2 | 13% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 4 | 27% |
| Medicine and Dentistry | 3 | 20% |
| Chemistry | 2 | 13% |
| Immunology and Microbiology | 2 | 13% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 1 | 7% |
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 21 May 2014.
All research outputs
#20,230,558
of 22,756,196 outputs
Outputs from Theoretical Biology and Medical Modelling
#246
of 287 outputs
Outputs of similar age
#191,950
of 226,345 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#9
of 15 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 1st percentile – i.e., 1% 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 226,345 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 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.