Stochastic Modeling and Bayesian Inference with Applications in Biophysics

Stochastic Modeling and Bayesian Inference with Applications in Biophysics

by Chao Du

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This thesis explores stochastic modeling and Bayesian inference strategies in the context of the following three problems: 1) Modeling the complex interactions between and within molecules; 2) Extracting information from stepwise signals that are commonly found in biophysical experiments; 3) Improving the computational efficiency of a non-parametric Bayesian inference algorithm.

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