Logistic functions replace Hill functions in gene regulatory network ODE models to ensure global smoothness, real-valued trajectories, positive basal production, and stable numerical integration across small and large networks.
Corrected hill function in stochastic gene regulatory networks
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Logistic functions serve as a robust replacement for Hill functions in GRN modeling by eliminating analytical pathologies for non-integer coefficients while preserving threshold sensitivity and enabling explicit well-posedness proofs.
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Logistic Gene Regulatory Networks: Prevention of Expression Shutdown, and Numerical Stability Beyond Hill Function
Logistic functions replace Hill functions in gene regulatory network ODE models to ensure global smoothness, real-valued trajectories, positive basal production, and stable numerical integration across small and large networks.
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Exploring Logistic Functions as Robust Alternatives to Hill Functions in Genetic Network Modeling
Logistic functions serve as a robust replacement for Hill functions in GRN modeling by eliminating analytical pathologies for non-integer coefficients while preserving threshold sensitivity and enabling explicit well-posedness proofs.