Bayesian analysis of folding and unfolding time series of single-forced RNAs

On the basis of a coarse-grain physical model of the folding and unfolding of single-forced RNAs conducted in light tweezer experiments, we theoretically investigate the feasibility of inferring the RNA's intrinsic kinetic parameters from the noisy time series of the molecule's extension. A Bayesian approach using Monte Carlo Markov Chain is proposed. We prove that this statistical approach is efficient and accurate in inferring the molecule's physical parameters, even if the experimental data are yielded under a narrow range of forces.