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Open Access Green as soon as Postprint is submitted to ZB.
Profile likelihood in systems biology.
FEBS J. 280, 2564-2571 (2013)
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.
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Publication type
Article: Journal article
Document type
Review
Keywords
Parameter Estimation ; Prediction ; Profile Likelihood ; Propagation Of Errors ; Uncertainty; Identifiability Analysis ; Predictions ; Reveals ; Models ; Range
ISSN (print) / ISBN
1742-464X
e-ISSN
1742-4658
Journal
FEBS Journal, The
Quellenangaben
Volume: 280,
Issue: 11,
Pages: 2564-2571
Publisher
Wiley
Non-patent literature
Publications
Reviewing status
Peer reviewed