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On the use of the moment equations for parameter inference, control and experimental design in stochastic biochemical reaction networks

Author(s):

J. Ruess, J. Lygeros
Conference/Journal:

Computational Methods in Systems Biology, vol. 8130 of Lecture Notes in Computer Science LNCS, pp. 1-4
Abstract:

Variability is present at all levels of biological systems. At the molecular level Brownian motion of the molecules leads to randomness of the biochemical reactions inside the cells. On a higher level, the molecular noise and other stochastic effects can lead to fundamentally different behavior of the cells in a population. As a consequence, average dynamics of a cell population are often not adequate to understand or control the dynamics of the population as a whole. We discuss how stochastic models of biochemical reaction networks which enable one to study heterogeneous cell populations can be identified from data and how experiments which make this identification as easy as possible can be designed.



Further Information
Year:

2013
Type of Publication:

Book Chapter
Supervisor:

J. Lygeros

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@incollection{
year={2013},
isbn={978-3-642-40707-9},
booktitle={Computational Methods in Systems Biology},
volume={8130},
series={Lecture Notes in Computer Science},
editor={Gupta, Ashutosh and Henzinger, ThomasA.},
doi={10.1007/978-3-642-40708-6_1},
title={On the Use of the Moment Equations for Parameter Inference, Control and Experimental Design in Stochastic Biochemical Reaction Networks},
url={http://dx.doi.org/10.1007/978-3-642-40708-6_1},
publisher={Springer Berlin Heidelberg},
author={Ruess, Jakob and Lygeros, John},
pages={1-4}
}
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