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

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The D reconstruction of the electron scattering intensity of a virus from cryo electron microscopy is essentially a 3D tomography problem in which the orientation of the 2D projections is unknown. Many biological problems concern mixtures of different types of virus particles or mixtures of different maturation states of the same type of virus particle. For a variety of reasons, especially low SNR, it can be very challenging to label the type or state shown in an individual image. Algorithms capable of computing multiple reconstructions, one for each type or state, based on images which are not labeled according to type or state, are described and demonstrated on experimental images.
    Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on 01/2005; 5. · 4.63 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Computational advances have significantly contributed to the current role of electron cryomicroscopy (cryoEM) in structural biology. The needs for computational power are constantly growing with the increasing complexity of algorithms and the amount of data needed to push the resolution limits. High performance computing (HPC) is becoming paramount in cryoEM to cope with those computational needs. Since the nineties, different HPC strategies have been proposed for some specific problems in cryoEM and, in fact, some of them are already available in common software packages. Nevertheless, the literature is scattered in the areas of computer science and structural biology. In this communication, the HPC approaches devised for the computation-intensive tasks in cryoEM (single particles and tomography) are retrospectively reviewed and the future trends are discussed. Moreover, the HPC capabilities available in the most common cryoEM packages are surveyed, as an evidence of the importance of HPC in addressing the future challenges.
    Journal of Structural Biology 08/2008; 164(1):1-6. · 3.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cryo-electron microscopy has recently been recognized as a useful alternative to obtain three-dimensional density maps of macro- molecular complexes, especially when crystallography and NMR tech- niques fail. The three-dimensional model is constructed from large collec- tions of cryo-electron microscopy images of identical particles in random (and unknown) orientations. The major problem with cryo-electron microscopy is that the images are very noisy as the signal-to-noise ratio can be below one. Thus, standard filtering techniques are not directly applicable. Traditionally, the problem of immense noise in the cryo-electron microscopy images has been tackled by clustering the images and computing the class averages. However, then one has to assume that the particles have only few preferred orientations. In this paper we propose a sound method for denoising cryo-electron microscopy images using their Radon transforms. The method assumes only that the images are from identical particles but nothing is assumed about the orientations of the particles. Our preliminary experiments show that the method can be used to improve the image quality even when the signal-to-noise ratio is very low.
    Computational Science and Its Applications - ICCSA 2005, International Conference, Singapore, May 9-12, 2005, Proceedings, Part IV; 01/2005