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
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Koeppl, Heinz ; Hafner, Marc ; Lu, James |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Mapping behavioral specifications to model parameters in synthetic biology |
| Sprache: | Englisch |
| Publikationsjahr: | 30 April 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 12 August 2013 |
| Ort der Erstveröffentlichung: | London |
| Verlag: | BioMed Central |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | BMC Bioinformatics |
| Jahrgang/Volume einer Zeitschrift: | 14 |
| (Heft-)Nummer: | S10 |
| Kollation: | 7 Seiten |
| DOI: | 10.26083/tuprints-00026717 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/26717 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (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. |
| ID-Nummer: | Artikel-ID: S9 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-267174 |
| Zusätzliche Informationen: | 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. |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie 600 Technik, Medizin, angewandte Wissenschaften > 621.3 Elektrotechnik, Elektronik |
| Hinterlegungsdatum: | 30 Apr 2024 09:09 |
| Letzte Änderung: | 13 Mai 2024 09:57 |
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| Suche nach Titel in: | TUfind oder in Google |
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