Comprehensive estimation of input signals and dynamics in biochemical reaction networks


Cellular information processing can be described mathematically using differential equations. Often, external stimulation of cells by compounds such as drugs or hormones leading to activation has to be considered. Mathematically, the stimulus is represented by a time-dependent input function. Parameters such as rate constants of the molecular interactions are often unknown and need to be estimated from experimental data, e.g. by maximum likelihood estimation. For this purpose, the input function has to be defined for all times of the integration interval. This is usually achieved by approximating the input by interpolation or smoothing of the measured data. This procedure is suboptimal since the input uncertainties are not considered in the estimation process which often leads to overoptimistic confidence intervals of the inferred parameters and the model dynamics.


Projects: A2: Integration of Signalling Pathways in Hepatocellular Response

Bioinformatics 28(18): i529-i534
11th Sep 2012

M Schelker, A Raue, J Timmer, C Kreutz

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[Andreas Raue] [Jens Timmer] [Clemens Kreutz]

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  • Created: 29th Oct 2012 at 10:19
  • Last updated: 24th Oct 2013 at 16:15

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