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Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells.

Paul F LangDavid R PenasJulio R BangaDaniel WeindlBela Novak
Published in: PLoS computational biology (2024)
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.
Keyphrases
  • cell cycle
  • cell proliferation
  • endothelial cells
  • oxidative stress
  • signaling pathway
  • big data
  • deep learning
  • transcription factor
  • artificial intelligence
  • cell cycle arrest