Huanrong Tang1, Sihan Wang1, Jianquan Ouyang1,*, Tianming Liu2
Journal on Big Data, Vol.4, No.1, pp. 61-76, 2022, DOI:10.32604/jbd.2022.028078
Abstract Cryo-Electron Microscopy (cryo-EM) has become a powerful method to study the structure and function of biological macromolecules. However, in clustering tasks based on the projection angle of particles in cryo-EM, the noise considerably affects the clustering results. Existing denoising algorithms are ineffective due to the extremely low signal-to-noise ratio (SNR) of cryo-EM images and the complexity of noise types. The noise of a single particle greatly influences the orientation estimation of the subsequent clustering task, and the result of the clustering task directly affects the accuracy of the 3D reconstruction. In this paper, we propose a construction method of cryo-EM… More >
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