Go-and-Back method: effective estimation of the hidden motion of proteins from single-molecule time series.
Go-and-Back method: effective estimation of the hidden motion of proteins from single-molecule time series.
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DOI：
10.1063/1.3574396
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发表时间：
2010-11
期刊：
影响因子：
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通讯作者：
Makito Miyazaki;T. Harada
中科院分区：
文献类型：
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作者：
Makito Miyazaki;T. Harada
我们提出了一种有效的方法来估计运动的蛋白质从运动的附加探针粒子在单分子实验。该框架自然地结合了朗之万动力学来计算蛋白质的最可能轨迹。通过使用扰动展开技术，我们实现了计算成本比传统的梯度下降法小3个数量级以上，而不会损失计算算法的简单性。我们提出了说明性的应用程序的方法，使用简单的单分子实验模型，并确认所提出的方法产生合理和稳定的估计，以一种高效的方式隐藏的运动。
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.