Cheng Jing, Zhang Xinzheng
National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Biophys Rep. 2021 Apr 30;7(2):152-158. doi: 10.52601/bpr.2021.210001.
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.
冷冻电子显微镜数据的频率相关信噪比会随频率和数据类型而显著变化。在数据处理的不同步骤中，具有不同信噪比的数据用于计算。因此，应设计基于特定信噪比的特定加权函数，以优化相应的计算。在此，我们通过最大化互相关系数的信噪比推导出了这些加权函数。我们用于精修的一些加权函数与现有软件包中使用的相似。然而，我们推导的用于运动校正、颗粒挑选以及重叠密度精修的加权函数与现有程序所采用的不同。我们的新加权函数可能会改善这些步骤中的计算。
