Go-and-Back method: Effective estimation of the hidden motion of proteins from single-molecule time series

Makito Miyazaki, Takahiro Harada

Research output: Contribution to journalArticle

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.

Original languageEnglish
Article number135104
JournalJournal of Chemical Physics
Volume134
Issue number13
DOIs
Publication statusPublished - 2011 Apr 7
Externally publishedYes

Fingerprint

Time series
proteins
Molecules
molecules
Proteins
Experiments
Trajectories
descent
estimating
trajectories
costs
Costs
perturbation
gradients
expansion
probes
estimates
Costs and Cost Analysis

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry
  • Medicine(all)

Cite this

Go-and-Back method : Effective estimation of the hidden motion of proteins from single-molecule time series. / Miyazaki, Makito; Harada, Takahiro.

In: Journal of Chemical Physics, Vol. 134, No. 13, 135104, 07.04.2011.

Research output: Contribution to journalArticle

@article{12fb691e3d84461687fdb073735bce24,
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.",
author = "Makito Miyazaki and Takahiro Harada",
year = "2011",
month = "4",
day = "7",
doi = "10.1063/1.3574396",
language = "English",
volume = "134",
journal = "Journal of Chemical Physics",
issn = "0021-9606",
publisher = "American Institute of Physics Publising LLC",
number = "13",

}

TY - JOUR

T1 - Go-and-Back method

T2 - Effective estimation of the hidden motion of proteins from single-molecule time series

AU - Miyazaki, Makito

AU - Harada, Takahiro

PY - 2011/4/7

Y1 - 2011/4/7

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79954521008&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79954521008&partnerID=8YFLogxK

U2 - 10.1063/1.3574396

DO - 10.1063/1.3574396

M3 - Article

C2 - 21476777

AN - SCOPUS:79954521008

VL - 134

JO - Journal of Chemical Physics

JF - Journal of Chemical Physics

SN - 0021-9606

IS - 13

M1 - 135104

ER -