2021
DOI: 10.1016/j.jtbi.2020.110511
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Bifurcation and sensitivity analysis reveal key drivers of multistability in a model of macrophage polarization

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Cited by 13 publications
(32 citation statements)
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“…The authors used ordinary differential equations and included self-stimulation and mutual-inhibition circuits between STAT1 and STAT6 (Figure 2E). They justified this choice because the individual steps are unknown; therefore, they assumed that responses in self-stimulation and inhibition are sigmoidal and can be modeled using a Hill function [39]. Despite its simplicity, the model exhibits complex dynamics.…”
Section: Current Evidence Pointing To Multistability In Macrophage Pr...mentioning
confidence: 99%
“…The authors used ordinary differential equations and included self-stimulation and mutual-inhibition circuits between STAT1 and STAT6 (Figure 2E). They justified this choice because the individual steps are unknown; therefore, they assumed that responses in self-stimulation and inhibition are sigmoidal and can be modeled using a Hill function [39]. Despite its simplicity, the model exhibits complex dynamics.…”
Section: Current Evidence Pointing To Multistability In Macrophage Pr...mentioning
confidence: 99%
“…To compare the numerical runtimes and clustering results of cPCCA+ and G-PCCA+, we consider the cases of (1) a circular transition matrix (taken and adapted from [13]; see Example 3.2 therein), and (2) the infinitesimal generator of a stochastic, non-reversible gene-regulatory network, generated from the model in [18].…”
Section: Comparison Of Numerical Runtimesmentioning
confidence: 99%
“…Stochastic gene-regulatory network. We transformed the 2-dimensional deterministic macrophage polarization model described in [18] into a stochastic gene-regulatory network whose dynamic is described by the Chemical Master Equation (CME). We analyze the system on a finite state space of size 2 for ∈ {20, 40, 60, 80, 100}.…”
Section: Comparison Of Numerical Runtimesmentioning
confidence: 99%
“…The authors used ordinary differential equations and included self-stimulation and a mutual-inhibition circuits between STAT1 and STAT6 (Figure 2E). They justified this choice because the individual steps are unknown, therefore they assumed that responses in self-stimulation and inhibition are sigmoidal and can be modeled using a Hill function [36]. Despite its simplicity, the model exhibits complex dynamics.…”
Section: Current Evidence Pointing To Bistability In Macrophage Programsmentioning
confidence: 99%