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.
Xue
Xiao Chuan
XC
Tong
Huan
H
Liu
Fei
F
Ou-Yang
Zhong-Can
ZC
D001499:Bayes Theorem; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D011487:Protein Conformation; D012313:RNA / Q000737:chemistry*
D012313:RNA