Napolitano, Sara (2021) Analysis and control of biomolecular networks by microfluidics. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Analysis and control of biomolecular networks by microfluidics |
| Autori: | Autore Email Napolitano, Sara sara.napolitano@unina.it |
| Data: | 15 Luglio 2021 |
| Numero di pagine: | 132 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Chimica, dei Materiali e della Produzione Industriale |
| Dottorato: | Ingegneria dei prodotti e dei processi industriali |
| Ciclo di dottorato: | 33 |
| Coordinatore del Corso di dottorato: | nome email D'Anna, Andrea anddanna@unina.it |
| Tutor: | nome email di Bernardo, Diego [non definito] |
| Data: | 15 Luglio 2021 |
| Numero di pagine: | 132 |
| Parole chiave: | Cybergenetics, Microfluidics, Signalling pathway, Cell-cycle, mTOR |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-IND/34 - Bioingegneria industriale |
| Depositato il: | 20 Lug 2021 12:03 |
| Ultima modifica: | 07 Giu 2023 11:19 |
| URI: | http://www.fedoa.unina.it/id/eprint/13766 |
Abstract
The process by which the cells respond and adapt to internal and external stimuli, is almost always controlled by a complex network of genes, proteins, small molecules, and their mutual interactions, called signalling network. Over the last years, it has become apparent that quantitative and methodological tools from Biomedical and Control Engineering can be used to understand how these networks work, but also to engineer "synthetic" networks to robustly steer cellular behavior in a prescribed fashion. This possibility will be transformative, enabling myriad applications in biotechnology, chemical industry, health and biomedicine, food, and the environment. Cybergenetics is a new discipline merging the tools of Synthetic Biology with those of Biomedical and Control Engineering, with the aim of building robust synthetic gene networks to engineer biological processes. This Thesis is within this research topic, and comprises two different applications, one in yeast cells and one in human cells: (1) closed-loop feedback control to synchronise the cell cycle across a population of yeast cells (Saccharomyces cerevisiae); (2) quantitative analysis and model of TFEB nuclear translocation dynamics following mTOR inhibition in human cells (HeLa).
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