Bayesian parameter estimation for biochemical reaction networks using region-based adaptive parallel tempering.

ABSTRACT:

Motivation

Mathematical models have become standard tools for the investigation of cellular processes and the unraveling of signal processing mechanisms. The parameters of these models are usually derived from the available data using optimization and sampling methods. However, the efficiency of these methods is limited by the properties of the mathematical model, e.g. non-identifiabilities, and the resulting posterior distribution. In particular, multi-modal distributions with long valleys or pronounced tails are difficult to optimize and sample. Thus, the developement or improvement of optimization and sampling methods is subject to ongoing research.

Results

We suggest a region-based adaptive parallel tempering algorithm which adapts to the problem-specific posterior distr

SUBMITTER: Ballnus B 

PROVIDER: S-EPMC6022572 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature