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Mapping behavioral specifications to model parameters in synthetic biology

Koeppl, Heinz ; Hafner, Marc ; Lu, James (2024)
Mapping behavioral specifications to model parameters in synthetic biology.
In: BMC Bioinformatics, 2013, 14 (S10)
doi: 10.26083/tuprints-00026717
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Mapping behavioral specifications to model parameters in synthetic biology
Language: English
Date: 30 April 2024
Place of Publication: Darmstadt
Year of primary publication: 12 August 2013
Place of primary publication: London
Publisher: BioMed Central
Journal or Publication Title: BMC Bioinformatics
Volume of the journal: 14
Issue Number: S10
Collation: 7 Seiten
DOI: 10.26083/tuprints-00026717
Corresponding Links:
Origin: Secondary publication service
Abstract:

With recent improvements of protocols for the assembly of transcriptional parts, synthetic biological devices can now more reliably be assembled according to a given design. The standardization of parts open up the way for in silico design tools that improve the construct and optimize devices with respect to given formal design specifications. The simplest such optimization is the selection of kinetic parameters and protein abundances such that the specified design constraints are robustly satisfied. In this work we address the problem of determining parameter values that fulfill specifications expressed in terms of a functional on the trajectories of a dynamical model. We solve this inverse problem by linearizing the forward operator that maps parameter sets to specifications, and then inverting it locally. This approach has two advantages over brute-force random sampling. First, the linearization approach allows us to map back intervals instead of points and second, every obtained value in the parameter region is satisfying the specifications by construction. The method is general and can hence be incorporated in a pipeline for the rational forward design of arbitrary devices in synthetic biology.

Identification Number: Artikel-ID: S9
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-267174
Additional Information:

This article has been published as part of BMC Bioinformatics Volume 14 Supplement 10, 2013: Selected articles from the 10th International Workshop on Computational Systems Biology (WCSB) 2013: Bioinformatics. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcbioinformatics/supplements/14/S10.

Classification DDC: 500 Science and mathematics > 570 Life sciences, biology
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Date Deposited: 30 Apr 2024 09:09
Last Modified: 30 Apr 2024 09:10
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/26717
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