Detalle de: Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells
| Title | Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells |
| Abstract |
The mammalian cell cycle is regulated by a well-studied but complex biochemical reaction system. Computational models provide a particularly systematic and systemic description of the mechanisms governing mammalian cell cycle control. By combining both state-of-the-art multiplexed experimental methods and powerful computational tools, this work aims at improving on these models along four dimensions: model structure, validation data, validation methodology and model reusability. We developed a comprehensive model structure of the full cell cycle that qualitatively explains the behaviour of human retinal pigment epithelial-1 cells. To estimate the model parameters, time courses of eight cell cycle regulators in two compartments were reconstructed from single cell snapshot measurements. After optimisation with a parallel global optimisation metaheuristic we obtained excellent agreements between simulations and measurements. The PEtab specification of the optimisation problem facilitates reuse of model, data and/or optimisation results. Future perturbation experiments will improve parameter identifiability and allow for testing model predictive power. Such a predictive model may aid in drug discovery for cell cycle-related disorders. |
| Apa Reference | Lang, P. F., Penas, D. R., Banga, J. R., Weindl, D., & Novak, B. (2024). Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells. PLOS Computational Biology, 20(1), e1011151. 10.1371/journal.pcbi.1011151 |
| Doi | 10.1371/journal.pcbi.1011151 |
| Publication Date | 8 Jan 2024 |
| Publication Type | Article |
| Researcher | Julio Rodriguez Banga |
| Ontology | Computational models and simulations, Biosystems Modeling, Drug Discovery and design, Single-cell omics |
| Research Groups | Computational Biology Lab at MBG |
| Tools |
