Set-based parameter estimation for symmetric network motifs
Set-based parameter estimation for symmetric network motifs
Deriving a predictive model in systems biology is a complex task. One major problem is the typically large network size, which renders the analysis with standard methods difficult. Symmetry, as omnipresent in nature, was used in many applications to encounter this problem. In this work, we investigate the influence of symmetry on set-based parameter estimation. We show that the presence of symmetry in a model can be used to significantly simplify the parameter estimation problem. This is done by determining a symmetry-adapted basis, corresponding to a linear representation of a finite group, in which the problem size is of smaller dimension. We demonstrate the applicability of this approach for several common network motifs, as e.g. the Michaelis-Menten reaction and the feedforward motif.
978-3-902661-93-7
10454-10459
International Federation of Automatic Control
Rumschinski, Philipp
d82c5ac5-50c5-4cef-aa76-13a972f73418
Laila, Dina Shona
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c
Borcher, Steffan
9ad67c51-af55-459b-bc80-8646a65d6934
Findeisen, Rolf
be2ca39b-6c04-494b-8f75-8b7247c5d974
29 August 2011
Rumschinski, Philipp
d82c5ac5-50c5-4cef-aa76-13a972f73418
Laila, Dina Shona
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c
Borcher, Steffan
9ad67c51-af55-459b-bc80-8646a65d6934
Findeisen, Rolf
be2ca39b-6c04-494b-8f75-8b7247c5d974
Rumschinski, Philipp, Laila, Dina Shona, Borcher, Steffan and Findeisen, Rolf
(2011)
Set-based parameter estimation for symmetric network motifs.
In Proceedings of Set-Based Parameter Estimation for Symmetric Network Motifs World Congress.
International Federation of Automatic Control.
.
(doi:10.3182/20110828-6-IT-1002.03108).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Deriving a predictive model in systems biology is a complex task. One major problem is the typically large network size, which renders the analysis with standard methods difficult. Symmetry, as omnipresent in nature, was used in many applications to encounter this problem. In this work, we investigate the influence of symmetry on set-based parameter estimation. We show that the presence of symmetry in a model can be used to significantly simplify the parameter estimation problem. This is done by determining a symmetry-adapted basis, corresponding to a linear representation of a finite group, in which the problem size is of smaller dimension. We demonstrate the applicability of this approach for several common network motifs, as e.g. the Michaelis-Menten reaction and the feedforward motif.
More information
Published date: 29 August 2011
Venue - Dates:
18th IFAC World Congress, Milan, Italy, 2011-08-28 - 2011-09-02
Organisations:
Mechatronics
Identifiers
Local EPrints ID: 353684
URI: http://eprints.soton.ac.uk/id/eprint/353684
ISBN: 978-3-902661-93-7
PURE UUID: 7895a1ee-84f7-4f76-bbc7-c6888aac462a
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Date deposited: 24 Jun 2013 13:37
Last modified: 14 Mar 2024 14:08
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Contributors
Author:
Philipp Rumschinski
Author:
Dina Shona Laila
Author:
Steffan Borcher
Author:
Rolf Findeisen
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