Simultaneous model selection and model calibration for the proliferation of tumor and normal cells during in vitro chemotherapy experiments

dc.contributor.author	Costa, José M.J.
dc.contributor.author	Orlande, Helcio R.B.
dc.contributor.author	Lione, Viviane O.F.
dc.contributor.author	Lima, Antonio G.F.
dc.contributor.author	Cardoso, Tayná C.S.
dc.contributor.author	Varón, Leonardo A.B.
dc.date.accessioned	2020-02-10T01:04:08Z
dc.date.available	2020-02-10T01:04:08Z
dc.date.issued	2018-12-06
dc.description.abstract	In vitro experiments were conducted in this work to analyze the proliferation of tumor (DU-145) and normal (macrophage RAW 264.7) cells under the influence of a chemotherapeutic drug (doxorubicin). Approximate Bayesian Computation (ABC) was used to select among four competing models to represent the number of cells and to estimate the model parameters, based on the experimental data. For one case, the selected model was validated in a replicated experiment, through the solution of a state estimation problem with a particle filter algorithm, thus demonstrating the robustness of the ABC procedure used in this work.	es
dc.identifier.issn	10665277
dc.identifier.uri	https://repositorio.usc.edu.co/handle/20.500.12421/2698
dc.language.iso	en	es
dc.publisher	Mary Ann Liebert Inc.	es
dc.subject	Approximate Bayesian computation	es
dc.subject	Chemotherapy	es
dc.subject	DU-145 cells	es
dc.subject	RAW 264.7 cells	es
dc.subject	State estimation	es
dc.title	Simultaneous model selection and model calibration for the proliferation of tumor and normal cells during in vitro chemotherapy experiments	es
dc.type	Article	es

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