ArticleNPJ systems biology and applications2023
Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.
Article in NPJ systems biology and applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The Emergent Architecture of Autonomous Clocks Described by Computational Algorithms of Regulatory Networks.Advances in experimental medicine and biology · 2026Article
- Multistability and predominant hybrid phenotypes in a four node mutually repressive network of Th1/Th2/Th17/Treg differentiation.NPJ systems biology and applications · 2024Article
- Network topology and interaction logic determine states it supports.NPJ systems biology and applications · 2024Review
- A yeast cell cycle pulse generator model shows consistency with multiple oscillatory and checkpoint mutant datasets.Mathematical biosciences · 2024Article
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6 authors.
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Abstract
Mathematical modeling of the emergent dynamics of gene regulatory networks (GRN) faces a double challenge of (a) dependence of model dynamics on parameters, and (b) lack of reliable experimentally determined parameters. In this paper we compare two complementary approaches for describing GRN dynamics across unknown parameters: (1) parameter sampling and resulting ensemble statistics used by RACIPE (RAndom CIrcuit PErturbation), and (2) use of rigorous analysis of combinatorial approximation of the ODE models by DSGRN (Dynamic Signatures Generated by Regulatory Networks). We find a very good agreement between RACIPE simulation and DSGRN predictions for four different 2- and 3-node networks typically observed in cellular decision making. This observation is remarkable since the DSGRN approach assumes that the Hill coefficients of the models are very high while RACIPE assumes the values in the range 1-6. Thus DSGRN parameter domains, explicitly defined by inequalities between systems parameters, are highly predictive of ODE model dynamics within a biologically reasonable range of parameters.
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