Topic 38
systems model mathematical dynamics parameters models framework experimental stochastic biophysics theoretical theory modeling computational simulations parameter how biological can networks network such time simple dynamical simulation based it system equations processes general paper problem noise experimentally properties numerical equation number nonlinear principles different find between predictions modelling author propose state space work experiments show approach linear distributions underlying describe perturbations develop reaction rate kinetic feedback derive growth analytical understanding be interactions reproduce steady account fundamental set diffusion information process complex optimal conditions this dimensional allows where biology predicts on constraints way introduce proposed states level scales robustness complexity understand fitting
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