La Regina, Antonella (2023) Microfluidic-based feedback control of biological systems for biotechnology and biomedical applications. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Microfluidic-based feedback control of biological systems for biotechnology and biomedical applications |
| Autori: | Autore Email La Regina, Antonella antonella.laregina@unina.it |
| Data: | 10 Marzo 2023 |
| Numero di pagine: | 119 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Elettrica e delle Tecnologie dell'Informazione |
| Dottorato: | Information and Communication Technology for Health |
| Ciclo di dottorato: | 35 |
| Coordinatore del Corso di dottorato: | nome email Riccio, Daniele daniele.riccio@unina.it |
| Tutor: | nome email di Bernardo, Mario [non definito] |
| Data: | 10 Marzo 2023 |
| Numero di pagine: | 119 |
| Parole chiave: | cybergenetics, microfluidic, yeast, stem cells |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/04 - Automatica |
| Depositato il: | 14 Apr 2023 07:59 |
| Ultima modifica: | 10 Apr 2025 12:42 |
| URI: | http://www.fedoa.unina.it/id/eprint/15068 |
Abstract
Cybergenetics is an emerging discipline that combines functionalities from synthetic biology and control engineering. The biological systems of interest, such as unicellular or multicellular organisms, are often unpredictable and unstable to characterize. Therefore, to increase the robustness and reliability of the system, typical tools from control theory, such as feedback loops, can be employed. In this work, we exploit how control engineering can be used to automatically steer complex biological processes towards desired behaviors with a microfluidics/microscopy platform. The platform allows to automatically regulate gene expression in real-time, in model-based or model-free scenario. Hence, cybergenetics tools, microfluidic-microscopy platforms, segmentation and control algorithms allow the precise tuning of such specific biological phenomena in different species such as yeast and mammals. Specifically, I will investigate the possibility to achieve long-term synchronization of cell population, by interfacing genetically modified yeast cells, and the precise tuning of mouse embryonic stem cells fate in a completely controllable automatized environment developing new protocols for long term culture.
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