Multiple events on single molecules: Unbiased estimation in single-molecule biophysics
Multiple events on single molecules: Unbiased estimation in single-molecule biophysics
复制标题
DOI：
10.1073/pnas.0510509103
复制
发表时间：
2006-02-07
影响因子：
11.1
通讯作者：
Dekker, NH
中科院分区：
文献类型：
--
作者：
Koster, DA;Wiggins, CH;Dekker, NH
单分子实验的大多数分析包括将实验结果合并到直方图中，并找到优化该直方图与给定数据模型的拟合的参数。在这里，我们表明这种方法可能会在参数估计中引入偏差，因此在根据实验数据估计模型参数时必须非常小心。当观察结果本身在统计上不独立并且受到全局约束时，例如，当作用于单个分子的运动蛋白的迭代步骤不得超过分子总长度时，偏差可能特别大。我们开发了最大似然分析，尊重实验约束，即使偏差远远超过 100%，也可以对参数进行稳健且无偏差的估计。我们展示了该方法在许多单分子实验中的潜力，重点是拓扑异构酶 IB 去除 DNA 超螺旋，并通过实验的数值模拟验证了该方法。
Most analyses of single-molecule experiments consist of binning experimental outcomes into a histogram and finding the parameters that optimize the fit of this histogram to a given data model. Here we show that such an approach can introduce biases in the estimation of the parameters, thus great care must be taken in the estimation of model parameters from the experimental data. The bias can be particularly large when the observations themselves are not statistically independent and are subjected to global constraints, as, for example, when the iterated steps of a motor protein acting on a single molecule must not exceed the total molecule length. We have developed a maximum-likelihood analysis, respecting the experimental constraints, which allows for a robust and unbiased estimation of the parameters, even when the bias well exceeds 100%. We demonstrate the potential of the method for a number of single-molecule experiments, focusing on the removal of DNA supercoils by topoisomerase IB, and validate the method by numerical simulation of the experiment.