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