Bayesian inference of chemical kinetic models from proposed reactions

Models of Oscillating Chemical Reactions. Particularities of Some Proposed Models for the Characterization of Chemical Oscillations

Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units

A goal of systems biology is to understand the dynamics of intracellular systems. Stochastic chemical kinetic models are often utilized to accurately capture the stochastic nature of these systems due to low numbers of molecules. Collecting system data allows for estimation of stochastic chemical kinetic rate parameters. We describe a well-known, but typically impractical data augmentation Mark...

On Bayesian Inference for Stochastic Kinetic Models using Diffusion Approximations

This paper is concerned with the Bayesian estimation of stochastic rate constants in the context of dynamic models of intra-cellular processes. The underlying discrete stochastic kinetic model is replaced by a diffusion approximation (or stochastic differential equation approach) where a white noise term models stochastic behaviour and the model is identified using equispaced time course data. ...

Bayesian inference for stochastic kinetic models using a diffusion approximation.

This article is concerned with the Bayesian estimation of stochastic rate constants in the context of dynamic models of intracellular processes. The underlying discrete stochastic kinetic model is replaced by a diffusion approximation (or stochastic differential equation approach) where a white noise term models stochastic behavior and the model is identified using equispaced time course data. ...

Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models

As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we explore the Bayesian estimation of stochastic kinetic rate constants governing dynamic models of intracellular processes. The underlying model is replaced by a diffusion approximation where a noise term represents intrinsi...