ArticleJournal of theoretical biology2012
Clustering in cell cycle dynamics with general response/signaling feedback.
Article in Journal of theoretical biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Instability of the steady state solution in cell cycle population structure models with feedback.Journal of mathematical biology · 2019Article
- Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms, and cancer drug design using big database mining and genome-wide next-generation sequencing data.Cell cycle (Georgetown, Tex.) · 2016Article
- Cell cycle Start is coupled to entry into the yeast metabolic cycle across diverse strains and growth rates.Molecular biology of the cell · 2016Article
- Cell cycle dynamics: clustering is universal in negative feedback systems.Journal of mathematical biology · 2015Article
- Noise-induced dispersion and breakup of clusters in cell cycle dynamics.Journal of theoretical biology · 2014Article
- Cell cycle dynamics in a response/signalling feedback system with a gap.Journal of biological dynamics · 2014Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call responsive/signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behavior of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as "uniform" solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments.
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Registered trials
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