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• W2949096511 abstract "Cell size is a key characteristic that significantly affects many aspects of cellular physiology. There are specific control mechanisms during cell cycle that maintain the cell size within a range from generation to generation. Such control mechanisms introduce substantial variabilities to important properties of the cell cycle such as growth and division. To quantitatively study the effect of such variability in progression through cell cycle, detailed stochastic models are required. In this paper, a new hybrid stochastic model is proposed to study the effect of molecular noise and size control mechanism on the variabilities in cell cycle of the budding yeast Saccharomyces cerevisiae. The proposed model provides an accurate, yet computationally efficient approach for simulation of an intricate system by integrating the deterministic and stochastic simulation schemes. The developed hybrid stochastic model can successfully capture several key features of the cell cycle observed in experimental data. In particular, the proposed model: 1) confirms that the majority of noise in size control stems from low copy numbers of transcripts in the G1 phase, 2) identifies the size and time regulation modules in the size control mechanism, and 3) conforms with phenotypes of early G1 mutants in exquisite detail. Hybrid stochastic modeling approach can be used to provide quantitative descriptions for stochastic properties of the cell cycle within a computationally efficient framework." @default.
• W2949096511 created "2019-06-27" @default.
• W2949096511 creator A5022834433 @default.
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• W2949096511 date "2019-06-01" @default.
• W2949096511 modified "2023-10-16" @default.
• W2949096511 title "A stochastic model of size control in the budding yeast cell cycle" @default.
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• W2949096511 doi "https://doi.org/10.1186/s12859-019-2839-9" @default.
• W2949096511 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6584508" @default.
• W2949096511 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31216979" @default.
• W2949096511 hasPublicationYear "2019" @default.
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