A stochastic model of proliferation of cancer stem cells and its estimation by particle filtering

In this paper, we propose a model for proliferation of cancer stem cells and a procedure for estimating the unknowns of the model. Understanding the proliferation of cancer stem cells is critical for the development of anti-cancer therapies. We propose to use a nonlinear and non-Gaussian state-space...

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Bibliographic Details
Published in2010 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 529 - 533
Main Authors Bugallo, Mónica F, Botchkina, Galina, Djurić, Petar M
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2010
Subjects
Biological system modeling
Cancer
cancer stem cells
Cells (biology)
Drugs
Evolution (biology)
Filtering
high dimensional systems
Medical treatment
Neoplasms
Particle filtering
sparse time series
Stem cells
Stochastic processes
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Summary:In this paper, we propose a model for proliferation of cancer stem cells and a procedure for estimating the unknowns of the model. Understanding the proliferation of cancer stem cells is critical for the development of anti-cancer therapies. We propose to use a nonlinear and non-Gaussian state-space model for studying the proliferation process. For estimation of the unknowns we apply particle filtering, which is particularly appropriate given the nature of the model. In addition, we deal with a very large dimension of the state-space and very sparse time series of measurements. Computer simulations show promising results in a simple scenario generated with synthetic data.
ISBN:9781424442959
1424442958
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2010.5495634