Deciphering signal transduction networks in the liver by mechanistic mathematical modelling.
Biochem J
; 479(12): 1361-1374, 2022 06 30.
Article
em En
| MEDLINE
| ID: mdl-35748700
ABSTRACT
In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biologia de Sistemas
/
Modelos Biológicos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Biochem J
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Alemanha