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Accounting for Extrinsic Variability in the Estimation of Stochastic Rate Constants

Author(s):

H. Koeppl, C. Zechner, A. Ganguly, S. Pelet, M. Peter
Conference/Journal:

International Journal of Robust & Nonlinear Control, vol. 22, no. 10, H.K. and C.Z. contributed equally to this work, Article first published online: 4 APR 2012
Abstract:

Single-cell recordings of transcriptional and post-transcriptional processes reveal the inherent stochasticity of cellular events. However, to a large extent the observed variability in isogenic cell populations is due to extrinsic factors, such as difference in expression capacity, cell volume and cell cycle stage - to name a few. Thus, such experimental data represents a convolution of effects from stochastic kinetics and extrinsic noise sources. Recent parameter inference schemes for single-cell data just account for variability due to molecular noise. Here we present a Bayesian inference scheme which de-convolutes the two sources of variability and enables us to obtain optimal estimates of stochastic rate constants of low copy-number events and extract statistical information about cell-to-cell variability. In contrast to previous attempts, we model extrinsic noise by a variability in the abundance of mass-conserved species, rather than a variability in kinetic parameters. We apply the scheme to a simple model of the osmo-stress induced transcriptional activation in budding yeast.

Year:

2012
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@Article { KoeEtal:2012:IFA_3905,
    author={H. Koeppl and C. Zechner and A. Ganguly and S. Pelet and M. Peter},
    title={{Accounting for Extrinsic Variability in the Estimation of
	  Stochastic Rate Constants}},
    journal={International Journal of Robust \& Nonlinear Control},
    year={2012},
    volume={22},
    number={10},
    pages={},
    month=jul,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3905}
}
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