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  Multistationarity in Mass Action Networks with Applications to ERK Activation

Conradi, C., & Flockerzi, D. (2012). Multistationarity in Mass Action Networks with Applications to ERK Activation. Journal of Mathematical Biology, 65(1), 107-156. doi:10.1007/s00285-011-0453-1.

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Conradi, Carsten1, Author           
Flockerzi, Dietrich2, Author           
Affiliations:
1Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              
2Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738154              

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 Abstract: Ordinary Differential Equations (ODEs) are an important tool in many areas of Quantitative Biology. For many ODE systems multistationarity (i.e. the existence of at least two positive steady states) is a desired feature. In general establishing multistationarity is a difficult task as realistic biological models are large in terms of states and (unknown) parameters and in most cases poorly parameterized (because of noisy measurement data of few components, a very small number of data points and only a limited number of repetitions). For mass action networks establishing multistationarity hence is equivalent to establishing the existence of at least two positive solutions of a large polynomial system with unknown coefficients. For mass action networks with certain structural properties, expressed in terms of the stoichiometric matrix and the reaction rate-exponent matrix, we present necessary and sufficient conditions for multistationarity that take the form of linear inequality systems. Solutions of these inequality systems define pairs of steady states and parameter values. We also present a sufficient condition to identify networks where the aforementioned conditions hold. To show the applicability of our results we analyse an ODE system that is defined by the mass action network describing the extracellular signal-regulated kinase (ERK) cascade (i.e. ERK-activation). © Springer, Part of Springer Science+Business Media [accessed 2013 July 2nd]

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Language(s): eng - English
 Dates: 2012
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: eDoc: 565058
Other: 48/12
DOI: 10.1007/s00285-011-0453-1
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Title: Journal of Mathematical Biology
Source Genre: Journal
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Pages: - Volume / Issue: 65 (1) Sequence Number: - Start / End Page: 107 - 156 Identifier: -