Characterizing heterogeneity among virus particles by stochastic 3D signal reconstruction

Nan Xu; Yunye Gong; Qiu Wang; Yili Zheng; Peter C. Doerschuk

doi:10.1117/12.2193791

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21 September 2015 Characterizing heterogeneity among virus particles by stochastic 3D signal reconstruction

Nan Xu, Yunye Gong, Qiu Wang, Yili Zheng, Peter C. Doerschuk

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Proceedings Volume 9600, Image Reconstruction from Incomplete Data VIII; 96000F (2015) https://doi.org/10.1117/12.2193791
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

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.

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Nan Xu, Yunye Gong, Qiu Wang, Yili Zheng, and Peter C. Doerschuk "Characterizing heterogeneity among virus particles by stochastic 3D signal reconstruction", Proc. SPIE 9600, Image Reconstruction from Incomplete Data VIII, 96000F (21 September 2015); https://doi.org/10.1117/12.2193791

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