Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods
Fig 3
(a) Using posterior samples from Eq (6). Even at smaller observation frequencies, the observed data is accurately captured, though (as expected) with greater uncertainty. (b) As Reactive SINDy estimates derivatives, errors in the numerical methods lead to large deviations in the reconstructed trajectories as sampling frequency and noise increase. Although a single trajectory at dt = 0.2 may capture the oscillating behavior, it is clearly biased away from the true observations.