ArticlePLoS computational biology2016
A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- A minimal model for the role of Rim4 in regulating meiotic exit in budding yeast.Molecular biology of the cell · 2026Article
- Using PyBioNetFit to leverage qualitative and quantitative data in biological model parameterization and uncertainty quantification.Frontiers in immunology · 2026Article
- Stochastic Boolean model of normal and aberrant cell cycles in budding yeast.NPJ systems biology and applications · 2024Article
- Modeling the START transition in the budding yeast cell cycle.PLoS computational biology · 2024Article
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production.PLoS computational biology · 2024Article
- Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor.Nature communications · 2023Article
- A continuous-time stochastic Boolean model provides a quantitative description of the budding yeast cell cycle.Scientific reports · 2022Article
- Random Parametric Perturbations of Gene Regulatory Circuit Uncover State Transitions in Cell Cycle.iScience · 2020Article
- Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants.NPJ systems biology and applications · 2020Article
- Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants.NPJ systems biology and applications · 2020Article
- Clb3-centered regulations are recurrent across distinct parameter regions in minimal autonomous cell cycle oscillator designs.NPJ systems biology and applications · 2020Article
- A hybrid stochastic model of the budding yeast cell cycle.NPJ systems biology and applications · 2020Article
- A stochastic model of size control in the budding yeast cell cycle.BMC bioinformatics · 2019Article
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- A transcriptome-wide analysis deciphers distinct roles of G1 cyclins in temporal organization of the yeast cell cycle.Scientific reports · 2019Article
- Mathematical modeling identifies Lck as a potential mediator for PD-1 induced inhibition of early TCR signaling.PloS one · 2018Article
- Modeling-Based Investigation of the Effect of Noise in Cellular Systems.Frontiers in molecular biosciences · 2018Review
- Parallel arrangements of positive feedback loops limit cell-to-cell variability in differentiation.PloS one · 2017Article
- Correction: A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.PLoS computational biology · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.