首页|Optimizing weighting functions for cryo-electron microscopy

Optimizing weighting functions for cryo-electron microscopy

扫码查看
原文链接
  • 万方数据
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 func-tions 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.

Cryo-electron microscopy (Cryo-EM)Cross correlation coefficient (CCC)Weighting function

Jing Cheng、Xinzheng Zhang

展开 >

National Laboratory of Biomacromolecules,CAS Center for Excellence in Biomacromolecules,Institute of Bio-physics,Chinese Academy of Sciences,Beijing 100101,China

University of Chinese Academy of Sciences,Beijing 100049,China

Center for Biological Imaging,CAS Center for Excellence in Biomacromolecules,Institute of Biophysics,Chinese Academy of Sciences,Beijing 100101,China

We thank L.Kong for cryo-EM data storage and backup,and Dr.Richard Haase,from Liwen Bianji,Edanz Group China (www.liwenbianji.cnfor editing the English text of a draft of this manuscript.The project was funded by the National Key R&D Program of ChinaNational Natural Science Foundation of ChinaStrategic Priority Research Program of the Chinese Academy of SciencesKey Research Program of Frontier Sciences at the Chinese Academy of SciencesX.Zhang received scholarships from the 'National Thousand (Young) Talents Program'from the Office of Global Experts Recruitment

2017YFA050470031930069XDB37040101ZDBS-LY-SM003

2021

生物物理学报
中国生物物理学会 中国科学院生物物理研究所

生物物理学报

影响因子：0.355
ISSN：1000-6737
年,卷(期)：2021.7(2)
  • 17