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Evaluation of Multitype Mathematical Models for CFSE-Labeling Experiment Data

Overview of attention for article published in Bulletin of Mathematical Biology, June 2011
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Title
Evaluation of Multitype Mathematical Models for CFSE-Labeling Experiment Data
Published in
Bulletin of Mathematical Biology, June 2011
DOI 10.1007/s11538-011-9668-y
Pubmed ID
Authors

Hongyu Miao, Xia Jin, Alan S. Perelson, Hulin Wu

Abstract

Carboxy-fluorescein diacetate succinimidyl ester (CFSE) labeling is an important experimental tool for measuring cell responses to extracellular signals in biomedical research. However, changes of the cell cycle (e.g., time to division) corresponding to different stimulations cannot be directly characterized from data collected in CFSE-labeling experiments. A number of independent studies have developed mathematical models as well as parameter estimation methods to better understand cell cycle kinetics based on CFSE data. However, when applying different models to the same data set, notable discrepancies in parameter estimates based on different models has become an issue of great concern. It is therefore important to compare existing models and make recommendations for practical use. For this purpose, we derived the analytic form of an age-dependent multitype branching process model. We then compared the performance of different models, namely branching process, cyton, Smith-Martin, and a linear birth-death ordinary differential equation (ODE) model via simulation studies. For fairness of model comparison, simulated data sets were generated using an agent-based simulation tool which is independent of the four models that are compared. The simulation study results suggest that the branching process model significantly outperforms the other three models over a wide range of parameter values. This model was then employed to understand the proliferation pattern of CD4+ and CD8+ T cells under polyclonal stimulation.

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Geographical breakdown

Country Count As %
United States 2 5%
United Kingdom 1 3%
Russia 1 3%
France 1 3%
Unknown 32 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 32%
Researcher 9 24%
Student > Bachelor 4 11%
Student > Master 3 8%
Student > Postgraduate 2 5%
Other 3 8%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 32%
Mathematics 9 24%
Medicine and Dentistry 3 8%
Biochemistry, Genetics and Molecular Biology 2 5%
Computer Science 2 5%
Other 3 8%
Unknown 6 16%
Attention Score in Context

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 20 April 2013.
All research outputs
#15,270,134
of 22,707,247 outputs
Outputs from Bulletin of Mathematical Biology
#720
of 1,092 outputs
Outputs of similar age
#83,158
of 114,081 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#1
of 1 outputs
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So far Altmetric has tracked 1,092 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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