@article{banks_sutton_thompson_bocharov_doumic_schenkel_argilaguet_giest_peligero_meyerhans_2011, title={A new model for the estimation of cell proliferation dynamics using CFSE data}, volume={373}, ISSN={["1872-7905"]}, DOI={10.1016/j.jim.2011.08.014}, abstractNote={CFSE analysis of a proliferating cell population is a popular tool for the study of cell division and divisionlinked changes in cell behavior. Recently Banks et al. (2011), Luzyanina et al. (2009), Luzyanina et al. (2007), a partial differential equation (PDE) model to describe lymphocyte dynamics in a CFSE proliferation assay was proposed. We present a significant revision of this model which improves the physiological understanding of several parameters. Namely, the parameter used previously as a heuristic explanation for the dilution of CFSE dye by cell division is replaced with a more physical component, cellular autofluorescence. The rate at which label decays is also quantified using a Gompertz decay process. We then demonstrate a revised method of fitting the model to the commonly used histogram representation of the data. It is shown that these improvements result in a model with a strong physiological basis which is fully capable of replicating the behavior observed in the data.}, number={1-2}, journal={JOURNAL OF IMMUNOLOGICAL METHODS}, author={Banks, H. T. and Sutton, Karyn L. and Thompson, W. Clayton and Bocharov, Gennady and Doumic, Marie and Schenkel, Tim and Argilaguet, Jordi and Giest, Sandra and Peligero, Cristina and Meyerhans, Andreas}, year={2011}, month={Oct}, pages={143–160} }
 @article{banks_sutton_thompson_bocharov_roose_schenkel_meyerhans_2011, title={Estimation of Cell Proliferation Dynamics Using CFSE Data}, volume={73}, ISSN={["1522-9602"]}, DOI={10.1007/s11538-010-9524-5}, abstractNote={Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57–89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1–26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experimental data. These investigations suggest that the new decay/label loss and time dependent effective proliferation and death rates do indeed provide improved fits of the model to data. Statistical models for the observed variability/noise in the data are discussed with implications for uncertainty quantification. The resulting new cell dynamics model should prove useful in proliferation assay tracking and modeling, with numerous applications in the biomedical sciences.}, number={1}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Banks, H. T. and Sutton, Karyn L. and Thompson, W. Clayton and Bocharov, Gennady and Roose, Dirk and Schenkel, Tim and Meyerhans, Andreas}, year={2011}, month={Jan}, pages={116–150} }
 @article{banks_rehm_sutton_2010, title={DYNAMIC SOCIAL NETWORK MODELS INCORPORATING STOCHASTICITY AND DELAYS}, volume={68}, ISSN={["1552-4485"]}, DOI={10.1090/s0033-569x-2010-01201-x}, abstractNote={Networks are typically studied via computational models, and often investigations are restricted to the static case. Here we extend the work in Banks, Karr, Nguyen and Samuels (2008), which demonstrated a simple dynamical system framework in which to study social network behavior, to include a discrete delay. This delay represents the time lag that is likely required for an agent to change his/her own characteristics (e.g., opinions, viewpoints or behavior) after interacting with an agent possessing different characteristics. Thus this modification adds significantly to the relevance of the model in many potential applications. We have shown that the delays can be incorporated into a stochastic differential equations (SDE) framework in an efficient and computationally tractable way. Through numerical studies, we see novel outcomes when stochasticity, delay, or both are considered, demonstrating the need to include these features should they be present in the network application.}, number={4}, journal={QUARTERLY OF APPLIED MATHEMATICS}, author={Banks, H. T. and Rehm, Keri and Sutton, Karyn L.}, year={2010}, month={Dec}, pages={783–802} }
 @article{banks_charles_jauffret_sutton_thompson_2010, title={Label structured cell proliferation models}, volume={23}, ISSN={["0893-9659"]}, DOI={10.1016/j.aml.2010.07.009}, abstractNote={We present a general class of cell population models that can be used to track the proliferation of cells which have been labeled with a fluorescent dye. The mathematical models employ fluorescence intensity as a structure variable to describe the evolution in time of the population density of proliferating cells. While cell division is a major component of changes in cellular fluorescence intensity, models developed here also address overall label degradation.}, number={12}, journal={APPLIED MATHEMATICS LETTERS}, author={Banks, H. T. and Charles, Frederique and Jauffret, Marie Doumic and Sutton, Karyn L. and Thompson, W. Clayton}, year={2010}, month={Dec}, pages={1412–1415} }