Marucci, Lucia (2010) Mathematical modelling and non-linear analysis of Synthetic Gene Regulatory Networks. [Tesi di dottorato] (Unpublished)
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Item Type: | Tesi di dottorato |
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Resource language: | English |
Title: | Mathematical modelling and non-linear analysis of Synthetic Gene Regulatory Networks |
Creators: | Creators Email Marucci, Lucia lucia.marucci@crg.es |
Date: | 29 November 2010 |
Number of Pages: | 182 |
Institution: | Università degli Studi di Napoli Federico II |
Department: | Informatica e sistemistica |
Scuola di dottorato: | Ingegneria dell'informazione |
Dottorato: | Ingegneria informatica ed automatica |
Ciclo di dottorato: | 23 |
Coordinatore del Corso di dottorato: | nome email Garofalo, Francesco franco.garofalo@unina.it |
Tutor: | nome email Di Bernardo, Diego dibernardo@tigem.it Di Bernardo, Mario mario.dibernardo@unina.it Santini, Stefania stsantin@unina.it |
Date: | 29 November 2010 |
Number of Pages: | 182 |
Keywords: | Synthetic Biology, dynamical systems, mathematical modelling, bifurcation theory. |
Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica |
Date Deposited: | 21 Dec 2010 14:20 |
Last Modified: | 04 Dec 2014 08:19 |
URI: | http://www.fedoa.unina.it/id/eprint/8146 |
DOI: | 10.6092/UNINA/FEDOA/8146 |
Collection description
The emerging discipline of Synthetic biology can be defined as the engineering of biology. The usefulness of a model in Synthetic biology lies in its ability to formalise the knowledge about the biological process at hand, to identify inconsistencies between hypotheses and observations, and to predict the behaviour of the biological process in yet untested conditions. The aim must be to develop holistic models which capture the essence of various interactions within the system and are able to analyse and give predictions of the system as a whole. From this perspective, the theory of dynamical systems and control can have a fundamental role in the analysis, modelling and design of synthetic biological circuits.
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