Profile likelihood in systems biology


Inferring knowledge about biological processes by a mathematical description is a major characteristic of Systems Biology. To understand and predict system's behavior the available experimental information is translated into a mathematical model. Since the availability of experimental data is often limited and measurements contain noise, it is essential to appropriately translate experimental uncertainty to model parameters as well as to model predictions. This is especially important in Systems Biology because typically large and complex models are applied and therefore the limited experimental knowledge might yield weakly specified model components. Likelihood profiles have been recently suggested and applied in the Systems Biology for assessing parameter and prediction uncertainty. In this article, the profile likelihood concept is reviewed and the potential of the approach is demonstrated for a model of the erythropoietin (EPO) receptor.


Projects: A2.3: Cross-talk and distinct properties of growth factor signalling reg..., A2.5: Integration of insulin and Wnt signalling in hepatocytes, A3.2: Cross-talk of signaling pathways and endocytic machinery in hepato...

FEBS J. 280(11): 2564-71
9th May 2013

Clemens Kreutz, Andreas Raue, Daniel Kaschek, Jens Timmer

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

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  • Created: 14th Jan 2014 at 11:37

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