Skip to main navigation Skip to search Skip to main content

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 non-linear 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.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages529-533
Number of pages5
ISBN (Print)9781424442966
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/TerritoryUnited States
CityDallas, TX
Period03/14/1003/19/10

Keywords

  • Cancer stem cells
  • High dimensional systems
  • Particle filtering
  • Sparse time series

Fingerprint

Dive into the research topics of 'A stochastic model of proliferation of cancer stem cells and its estimation by particle filtering'. Together they form a unique fingerprint.

Cite this