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.
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Research Article| April 07 2011
Go-and-Back method: Effective estimation of the hidden motion of proteins from single-molecule time series
Makito Miyazaki, Takahiro Harada; Go-and-Back method: Effective estimation of the hidden motion of proteins from single-molecule time series. J. Chem. Phys. 7 April 2011; 134 (13): 135104. https://doi.org/10.1063/1.3574396
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