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Estimating Lymphocyte Division and Death Rates from CFSE Data

Overview of attention for article published in Bulletin of Mathematical Biology, May 2006
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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3 patents
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1 Wikipedia page

Citations

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94 Mendeley
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3 CiteULike
Title
Estimating Lymphocyte Division and Death Rates from CFSE Data
Published in
Bulletin of Mathematical Biology, May 2006
DOI 10.1007/s11538-006-9094-8
Pubmed ID
Authors

Rob J. De Boer, Vitaly V. Ganusov, Dejan Milutinović, Philip D. Hodgkin, Alan S. Perelson

Abstract

The division tracking dye, carboxyfluorescin diacetate succinimidyl ester (CFSE) is currently the most informative labeling technique for characterizing the division history of cells in the immune system. Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] have pioneered the quantitative analysis of CFSE data. We confirm and extend their data analysis approach using simple mathematical models. We employ the extended Gett and Hodgkin [Nat. Immunol. 1:239-244, 2000] method to estimate the time to first division, the fraction of cells recruited into division, the cell cycle time, and the average death rate from CFSE data on T cells stimulated under different concentrations of IL-2. The same data is also fitted with a simple mathematical model that we derived by reformulating the numerical model of Deenick et al. [J. Immunol. 170:4963-4972, 2003]. By a non-linear fitting procedure we estimate parameter values and confidence intervals to identify the parameters that are influenced by the IL-2 concentration. We obtain a significantly better fit to the data when we assume that the T cell death rate depends on the number of divisions cells have completed. We provide an outlook on future work that involves extending the Deenick et al. [J. Immunol. 170:4963-4972, 2003] model into the classical smith-martin model, and into a model with arbitrary probability distributions for death and division through subsequent divisions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 6%
Portugal 1 1%
Australia 1 1%
Mexico 1 1%
United Kingdom 1 1%
Korea, Republic of 1 1%
Romania 1 1%
Unknown 82 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 22%
Researcher 21 22%
Student > Master 10 11%
Student > Doctoral Student 7 7%
Professor > Associate Professor 6 6%
Other 19 20%
Unknown 10 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 30%
Medicine and Dentistry 13 14%
Immunology and Microbiology 10 11%
Mathematics 7 7%
Biochemistry, Genetics and Molecular Biology 7 7%
Other 17 18%
Unknown 12 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 December 2020.
All research outputs
#3,272,274
of 22,787,797 outputs
Outputs from Bulletin of Mathematical Biology
#98
of 1,094 outputs
Outputs of similar age
#7,049
of 65,838 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#2
of 11 outputs
Altmetric has tracked 22,787,797 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,094 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 90% of its peers.
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 65,838 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.