ArticleBulletin of mathematical biology2012
Evaluation of multitype mathematical models for CFSE-labeling experiment data.
Article in Bulletin of mathematical biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Probabilistic modeling of cell cycle dynamics in response to cell cycle targeting chemotherapy drugs to guide treatment strategies.PLoS computational biology · 2025Article
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- A modified SEIR model with a jump in the transmission parameter applied to COVID-19 data on Wuhan.Stat (International Statistical Institute) · 2022Article
- Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance.Frontiers in bioinformatics · 2021Article
- Tissue-Resident Memory T Cells in Mice and Humans: Towards a Quantitative Ecology.Journal of immunology (Baltimore, Md. : 1950) · 2019Review
- Modeling cell population dynamics.In silico biology · 2019Article
- Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling.PloS one · 2017Article
- Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry.PloS one · 2016Article
- A Stochastic Model for CD4+ T Cell Proliferation and Dissemination Network in Primary Immune Response.PloS one · 2015Article
- Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division.Journal of mathematical biology · 2014Article
- Generalized Ordinary Differential Equation Models.Journal of the American Statistical Association · 2014Article
- Modeling the dynamics and migratory pathways of virus-specific antibody-secreting cell populations in primary influenza infection.PloS one · 2014Article
- EBNA3C-mediated regulation of aurora kinase B contributes to Epstein-Barr virus-induced B-cell proliferation through modulation of the activities of the retinoblastoma protein and apoptotic caspases.Journal of virology · 2013Article
- Asymmetry of Cell Division in CFSE-Based Lymphocyte Proliferation Analysis.Frontiers in immunology · 2013Review
- Quantifying T lymphocyte turnover.Journal of theoretical biology · 2013Article
- A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations.Journal of the Royal Society, Interface · 2013Article
- A novel statistical analysis and interpretation of flow cytometry data.Journal of biological dynamics · 2013Article
- FlowMax: A Computational Tool for Maximum Likelihood Deconvolution of CFSE Time Courses.PloS one · 2013Article
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Authors and funding
4 authors.
Funding
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.