ArticlePLoS computational biology2021
A modular approach for modeling the cell cycle based on functional response curves.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Interdependency of estradiol-mediated ERα activation and subsequent PR and GREB1 induction to control cell cycle progression.Heliyon · 2024Article
- R-loop and diseases: the cell cycle matters.Molecular cancer · 2024Review
- From biological data to oscillator models using SINDy.iScience · 2024Article
- Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells.PLoS computational biology · 2024Article
- BioModels' Model of the Year 2023.Frontiers in systems biology · 2024Article
- The ups and downs of biological oscillators: a comparison of time-delayed negative feedback mechanisms.Journal of the Royal Society, Interface · 2023Article
- Cell cycle oscillations driven by two interlinked bistable switches.Molecular biology of the cell · 2023Article
- Spatially coordinated collective phosphorylation filters spatiotemporal noises for precise circadian timekeeping.iScience · 2023Article
- Pseudo-nullclines enable the analysis and prediction of signaling model dynamics.Frontiers in cell and developmental biology · 2023Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modeling biochemical reactions by means of differential equations often results in systems with a large number of variables and parameters. As this might complicate the interpretation and generalization of the obtained results, it is often desirable to reduce the complexity of the model. One way to accomplish this is by replacing the detailed reaction mechanisms of certain modules in the model by a mathematical expression that qualitatively describes the dynamical behavior of these modules. Such an approach has been widely adopted for ultrasensitive responses, for which underlying reaction mechanisms are often replaced by a single Hill function. Also time delays are usually accounted for by using an explicit delay in delay differential equations. In contrast, however, S-shaped response curves, which by definition have multiple output values for certain input values and are often encountered in bistable systems, are not easily modeled in such an explicit way. Here, we extend the classical Hill function into a mathematical expression that can be used to describe both ultrasensitive and S-shaped responses. We show how three ubiquitous modules (ultrasensitive responses, S-shaped responses and time delays) can be combined in different configurations and explore the dynamics of these systems. As an example, we apply our strategy to set up a model of the cell cycle consisting of multiple bistable switches, which can incorporate events such as DNA damage and coupling to the circadian clock in a phenomenological way.
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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.