Properties of cell death models calibrated and compared using Bayesian approaches.

ABSTRACT: Using models to simulate and analyze biological networks requires principled approaches to parameter estimation and model discrimination. We use Bayesian and Monte Carlo methods to recover the full probability distributions of free parameters (initial protein concentrations and rate constants) for mass-action models of receptor-mediated cell death. The width of the individual parameter distributions is largely determined by non-identifiability but covariation among parameters, even those that are poorly determined, encodes essential information. Knowledge of joint parameter distributions makes it possible to compute the uncertainty of model-based predictions whereas ignoring it (e.g., by treating parameters as a simple list of values and variances) yields nonsensical predictions. Computing

SUBMITTER: Eydgahi H 

PROVIDER: S-EPMC3588908 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature