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  Model discrimination and parameter estimation via infeasibility certificates for dynamical biochemical reaction networks

Borchers, S., Rumschinski, P., Bosio, S., Weismantel, R., & Findeisen, R. (2009). Model discrimination and parameter estimation via infeasibility certificates for dynamical biochemical reaction networks. IFAC Proceedings Volumes, 42(10), 245-250.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-C6E3-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-38B8-1
Genre: Conference Paper

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This publication is with permission of the rights owner freely accessible on MPG.PuRe. Copyright © IFAC
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 Creators:
Borchers, Steffen1, 2, Author              
Rumschinski, Philipp1, 2, Author              
Bosio, S.2, Author
Weismantel, Robert2, Author
Findeisen, Rolf2, Author
Affiliations:
1International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738143              
2Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              

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 Abstract: Current approaches to parameter estimation and model invalidation are often inappropriate for biochemical reaction networks. This is because often only noisy measurements and sparse experimental data is available, and since they do not take the special structure of biochemical reaction networks into account. In this work a new method to prove model invalidity and to estimate parameters is introduced. It is based on a certificate of non-existence of feasible parameterizations for a given models. This is done by reformulating the model invalidation task into a set-based feasibility problem. As shown, due to the polynomial structure of many biochemical reaction systems, it is possible to relax the non-convex feasibility problem into a semidefinite program and thus to obtain conclusive results on model invalidity and parameter estimation. Our framework allows us to consider the arising difficulties posed by biochemical reaction networks by taking the specific structure of the dynamics and model outputs into account. It also enables us to discard large parameter regions as infeasible. We also show on a well-known biological example, namely the Michaelis-Menten and the Henri kinetics, how with this method it is possible to discriminate between model hypotheses and how to estimate parameters.

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Language(s): eng - English
 Dates: 2009
 Publication Status: Published in print
 Pages: -
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 Rev. Method: Peer
 Identifiers: eDoc: 441351
DOI: 10.3182/20090706-3-FR-2004.0386
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Title: 15th IFAC Symposium on System Identification SYSID
Place of Event: Saint-Malo, France
Start-/End Date: 2009-07-06 - 2009-07-08

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Title: IFAC Proceedings Volumes
Source Genre: Journal
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Pages: - Volume / Issue: 42 (10) Sequence Number: - Start / End Page: 245 - 250 Identifier: -