Rocco, Caggiano (2021) In silico simulation of tumor cell proliferation and movement based on biochemical models of mapk cascade. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | In silico simulation of tumor cell proliferation and movement based on biochemical models of mapk cascade |
| Autori: | Autore Email Rocco, Caggiano rocco.caggiano@unina.it |
| Data: | 15 Luglio 2021 |
| Numero di pagine: | 83 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Medicina Molecolare e Biotecnologie Mediche |
| Dottorato: | Medicina molecolare e biotecnologie mediche |
| Ciclo di dottorato: | 33 |
| Coordinatore del Corso di dottorato: | nome email Massimo, Santoro masantor@unina.it |
| Tutor: | nome email Giovanni, Paolella [non definito] |
| Data: | 15 Luglio 2021 |
| Numero di pagine: | 83 |
| Parole chiave: | systems biology, MAPK, proliferation |
| Settori scientifico-disciplinari del MIUR: | Area 05 - Scienze biologiche > BIO/10 - Biochimica |
| Depositato il: | 19 Lug 2021 11:05 |
| Ultima modifica: | 07 Giu 2023 11:26 |
| URI: | http://www.fedoa.unina.it/id/eprint/13589 |
Abstract
Systems biology allows analytical investigation of intracellular dynamics, analyzing complex processes and taking into account the interactions among the various subsystems. In this study, biochemical models describing the behavior of regulatory molecular networks were created and interfaced with a simulation system able to reproduce motility and proliferation of eukaryotic cell cultures. The primary focus was on MAPK cascades, particularly Erk1/2 activation by growth factors and mitogens such as EGF through tyrosine kinase receptors (RTKs) as Egfr, which represent a fundamental signal transduction and regulatory network affecting many cellular processes, including proliferation, motility, differentiation and survival. Erk1/2 predicted levels were related to reactions representing the progression of the cell cycle and used to modulate cell growth in a cell simulator. The biochemical model was built starting from literature data and a database of estimated protein concentrations representative of different cell types and experimental conditions and may be run for prolonged time frames and in various experimental conditions, including a vast array of cell lines. A software tool developed on purpose is able to run the model and interface with the cell simulator.
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