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Clustering and Averaging of Images in Single-Particle Analysis
Genome Informatics Series
Single particle analysis is a straightforward method for studying the structures of macromolecules that cannot be crystallized. It builds three-dimensional structures of particles by estimating the projection angles of their randomly oriented electron-microscopic images. The existing methods divide the images into clusters, build class averages for the clusters, and estimate the projection angle of each cluster. However, the clustering and the averaged images are highly sensitive to the choicedoi:10.11234/gi1990.11.151 fatcat:d6wcbgxdvrdxdjbkxgzksnkr3u