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Proceedings Paper

Characterizing heterogeneity among virus particles by stochastic 3D signal reconstruction
Author(s): Nan Xu; Yunye Gong; Qiu Wang; Yili Zheng; Peter C. Doerschuk
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Paper Abstract

In single-particle cryo electron microscopy, many electron microscope images each of a single instance of a biological particle such as a virus or a ribosome are measured and the 3-D electron scattering intensity of the particle is reconstructed by computation. Because each instance of the particle is imaged separately, it should be possible to characterize the heterogeneity of the different instances of the particle as well as a nominal reconstruction of the particle. In this paper, such an algorithm is described and demonstrated on the bacteriophage Hong Kong 97. The algorithm is a statistical maximum likelihood estimator computed by an expectation maximization algorithm implemented in Matlab software.

Paper Details

Date Published: 21 September 2015
PDF: 11 pages
Proc. SPIE 9600, Image Reconstruction from Incomplete Data VIII, 96000F (21 September 2015); doi: 10.1117/12.2193791
Show Author Affiliations
Nan Xu, Cornell Univ. (United States)
Yunye Gong, Cornell Univ. (United States)
Qiu Wang, Cornell Univ. (United States)
Siemens Corp. (United States)
Yili Zheng, Lawrence Berkeley National Lab. (United States)
Peter C. Doerschuk, Cornell Univ. (United States)


Published in SPIE Proceedings Vol. 9600:
Image Reconstruction from Incomplete Data VIII
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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