ArticlePloS one2016
A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Stochastic Boolean model of normal and aberrant cell cycles in budding yeast.NPJ systems biology and applications · 2024Article
- Cell Cycle Complexity: Exploring the Structure of Persistent Subsystems in 414 Models.Biomedicines · 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
- Design patterns for the construction of computational biological models.Briefings in bioinformatics · 2024Article
- Evolutionary Stability of Small Molecular Regulatory Networks That Exhibit Near-Perfect Adaptation.Biology · 2023Article
- A continuous-time stochastic Boolean model provides a quantitative description of the budding yeast cell cycle.Scientific reports · 2022Article
- Modeling and analysis of the macronutrient signaling network in budding yeast.Molecular biology of the cell · 2021Article
- A hybrid stochastic model of the budding yeast cell cycle.NPJ systems biology and applications · 2020Article
- Article
- Using both qualitative and quantitative data in parameter identification for systems biology models.Nature communications · 2018Article
- Mathematical Analysis of Cytokine-Induced Differentiation of Granulocyte-Monocyte Progenitor Cells.Frontiers in immunology · 2018Article
- Predicting network modules of cell cycle regulators using relative protein abundance statistics.BMC systems biology · 2017Article
- A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.PLoS computational biology · 2016Article
- Extended Robust Boolean Network of Budding Yeast Cell Cycle.Journal of medical signals and sensorsArticle
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Authors and funding
4 authors.
Funding
Abstract
To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.
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