title: Go-and-Back method: effective estimation of the hidden motion of proteins from single-molecule time series.
abstract: We present an effective method for estimating the motion of proteins from the motion of attached probe particles in single-molecule experiments. The framework naturally incorporates Langevin dynamics to compute the most probable trajectory of the protein. By using a perturbation expansion technique, we achieve computational costs more than 3 orders of magnitude smaller than the conventional gradient descent method without loss of simplicity in the computation algorithm. We present illustrative applications of the method using simple models of single-molecule experiments and confirm that the proposed method yields reasonable and stable estimates of the hidden motion in a highly efficient manner.
authors.affiliation: Department of Physics, Graduate School of Science, Kyoto University, Kyoto, Japan. miyazaki@chem.scphys.kyoto-u.ac.jp
authors.forename: Makito
authors.initials: M
authors.lastname: Miyazaki
authors.forename: Takahiro
authors.initials: T
authors.lastname: Harada
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D007700:Kinetics; D008956:Models, Chemical; D009038:Motion; D011336:Probability; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins