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- W2051724470 abstract "Instances of biological macromolecular complexes that have identical chemical constituents may not have thesame geometry due to, for example, flexibility. Cryo electron microscopy provides one noisy projection imageof each of many instances of a complex where the projection directions for the different instances are random.The noise is sufficient severe (SNR << 1) that the projection direction for a particular image cannot be easilyestimated from the individual image. The goal is to determine the 3-D geometry of the complex (the 3-Ddistribution of electron scattering intensity) which requires fusing information from these many images of manycomplexes. In order to describe the geometric heterogeneity of the complexes, the complex is described as aweighted sum of basis functions where the weights are random. In order to get tractable algorithms, the weightsare modeled as Gaussian random variables with unknown statistics and the noise is modeled as additive Gaussianrandom variables with unknown covariance. The statistics of the weights and the statistics of the noise are jointlyestimated by maximum likelihood by a generalized expectation maximization algorithm. The method has beendeveloped to the point where it appears able to solve problems of interest to the structural biology community." @default.
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- W2051724470 date "2012-02-09" @default.
- W2051724470 modified "2023-09-23" @default.
- W2051724470 title "3D reconstruction based on single-particle cryo electron microscopy images as a random signal in noise problem" @default.
- W2051724470 doi "https://doi.org/10.1117/12.917835" @default.
- W2051724470 hasPublicationYear "2012" @default.
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