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Correction: Bayesian parameter estimation for dynamical models in systems biology

  • Nathaniel J. Linden,
  • Boris Kramer,
  • Padmini Rangamani
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In section 1.6 Constrained interval unscented Kalman filter Markov chain Monte Carlo (CIUKF-MCMC) of the Materials and Methods section, there is an error in Theorem 1. Specifically, in several of the equations in the theorem, some of the indices on x and y in the exponents are incorrect. Please find the correct theorem below;

Theorem 1 (Marginal likelihood (Theorem 1 of [26] and 12.1 of [67])) Let yk denote the set of all observations up to time tk as defined in Section 1.2. Let the initial condition be uncertain with distribution p (x0|θ). Then the marginal likelihood is defined recursively in three stages:

for k = 1,2,…

  1. Predict the new state from previous data
  2. update the prediction with the current data
  3. and marginalize out uncertainty in the states

Reference

  1. 1. Linden NJ, Kramer B, Rangamani P (2022) Bayesian parameter estimation for dynamical models in systems biology. PLoS Comput Biol 18(10): e1010651. https://doi.org/10.1371/journal.pcbi.1010651 pmid:36269772