Parallel computing strategies for determining viral capsid structure by cryoelectron microscopy

US Nat. Inst. of Health
IEEE Computational Science and Engineering 05/1998; DOI: 10.1109/99.683745
Source: IEEE Xplore

ABSTRACT To calculate a full 3D structural model of a virus capsid,
researchers analyzed cryoelectron micrographs that contain many randomly
oriented images of the views. The authors use parallel computing
techniques to improve the performance of the computational algorithms
that determine each particle's orientation and generate the 3D model.
This enhanced computational performance allows analysis of many more
particles and a more precise determination of their orientations,
letting researchers study important details of virus capsids at higher

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    ABSTRACT: In this report we study the problem of determining three-dimensional orientations for noisy projections of randomly oriented identical particles. The problem is of central importance in the tomographic reconstruction of the density map of macromolecular complexes from electron microscope images and it has been studied intensively for more than 30 years. We analyze the computational complexity of the orientation problem and show that while several variants of the problem are $NP$-hard, inapproximable and fixed-parameter intractable, some restrictions are polynomial-time approximable within a constant factor or even solvable in logarithmic space. The orientation search problem is formalized as a constrained line arrangement problem that is of independent interest. The negative complexity results give a partial justification for the heuristic methods used in orientation search, and the positive complexity results on the orientation search have some positive implications also to the problem of finding functionally analogous genes. A preliminary version ``The Computational Complexity of Orientation Search in Cryo-Electron Microscopy'' appeared in Proc. ICCS 2004, LNCS 3036, pp. 231--238. Springer-Verlag 2004.
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    ABSTRACT: A statistical model for the object and the complete image formation process in the cryo electron microscopy of viruses is presented. Using this model, maximum-likelihood reconstructions of the three-dimensional (3-D) structure of viruses are computed using the expectation maximization algorithm, and alternative experimental designs are evaluated based on Cramer-Rao bounds. Numerical examples of the reconstructions and experimental design evaluations are provided based on Cowpea mosaic virus
    IEEE Transactions on Information Theory 09/2000; · 2.62 Impact Factor
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    ABSTRACT: Cryo electron microscopy is a measurement modality which provides images from which 3-D reconstructions of biological particles such as viruses can be estimated. When the specimen is composed of mixtures of particles of different types, the 3-D reconstruction problem must be solved jointly with a pattern classification problem. The performance of the estimators is not well understood because the computations are not suitable for analytical results and are too large for extensive Monte Carlo results. The problem formulation typically has nuisance parameters and different treatments of the nuisance parameters lead to different estimators. In this paper two types of estimators and two model problems are studied with the conclusion that it is difficult to improve upon maximum likelihood estimators based on integrating out the nuisance parameters.