Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.


Accounting for Extrinsic Variability in the Estimation of Stochastic Rate Constants


H. Koeppl, C. Zechner, A. Ganguly, S. Pelet, M. Peter

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

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.


Type of Publication:


File Download:

Request a copy of this publication.
(Uses JavaScript)
% 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},
Permanent link