A Stochastic Hill Climbing Approach for Simultaneous 2D Alignment and Clustering of Cryogenic Electron Microscopy Images
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文摘

Generation of improved 2D class averages from large single-particle cryo-EM datasets

Production of a reliable 3D starting model in a rapid and unbiased fashion

Overcoming inherent limitations in widely used clustering approaches

The method is many times faster than other widely used approaches

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