Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data

doi:10.1371/journal.pcbi.1011135

Filter inference: A scalable nonlinear mixed effects inference approach for snapshot time series data

Fig 6

Inference results of EGF pathway model II.

A: Shows the joint posterior distribution of the mean activation rate, , and the deactivation rate, from Fig 5B. B: Shows the inferred posterior distribution and the inferred population distribution from a separate inference run, where we fixed the deactivation rate to its data-generating value. All other inference settings, including data and priors, remain unchanged from the inference approach used to generate Fig 5.

doi: https://doi.org/10.1371/journal.pcbi.1011135.g006