PDF(Pubmed)
Abstract：
The frequency-dependent signal to noise ratio of cryo-electron microscopy data varies dramatically with the frequency and with the type of the data. During different steps of data processing, data with distinct SNR are used for calculations. Thus, specific weighting function based on the particular SNR should be designed to optimize the corresponding calculation. Here, we deduced these weighting functions by maximizing the signal to noise ratio of cross correlated coefficients. Some of our weighting functions for refinement resemble that used in the existing software packages. However, weighting functions we deduced for motion correction, particle picking and the refinement with overlapping densities differ from those employed by existing programs. Our new weighting functions may improve the calculation in these steps.
摘要：
低温电子显微镜数据的频率相关信噪比随频率和数据类型而急剧变化。在数据处理的不同步骤中，具有不同SNR的数据用于计算。因此，基于特定SNR的特定加权函数应设计为优化相应的计算。这里,我们通过最大化互相相关系数的信噪比来推导这些加权函数。我们用于细化的一些加权函数类似于现有软件包中使用的加权函数。然而,我们推导出用于运动校正的加权函数，粒子拾取和具有重叠密度的细化与现有程序所采用的不同。我们新的加权函数可以改进这些步骤中的计算。
