It's Likelihood-Free

Researchers led by Imperial College London's Oliver Ratmann developed a new model-based way to use Bayesian inference to study biological network data. In PLoS Computational Biology, they report that their approach uses the Approximate Bayesian Computation, or Likelihood-Free Inference and a MCMC algorithm to ascertain the distribution of the model's parameters.

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