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Helical reconstruction in RELION

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      We describe a new implementation for the reconstruction of helical assemblies in the empirical Bayesian framework of RELION. Our approach calculates optimal linear filters for the 3D reconstruction by embedding helical symmetry operators in Fourier-space, and deals with deviations from perfect helical symmetry through Gaussian-shaped priors on the orientations of individual segments. By incorporating our approach into the standard pipeline for single-particle analysis in RELION, our implementation aims to be easily accessible for non-experienced users. Although our implementation does not solve the problem that grossly incorrect structures can be obtained when the wrong helical symmetry is imposed, we show for four different test cases that it is capable of reconstructing structures to near-atomic resolution.

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      Most cited references 45

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      RELION: Implementation of a Bayesian approach to cryo-EM structure determination

       Sjors Scheres (2012)
      RELION, for REgularized LIkelihood OptimizatioN, is an open-source computer program for the refinement of macromolecular structures by single-particle analysis of electron cryo-microscopy (cryo-EM) data. Whereas alternative approaches often rely on user expertise for the tuning of parameters, RELION uses a Bayesian approach to infer parameters of a statistical model from the data. This paper describes developments that reduce the computational costs of the underlying maximum a posteriori (MAP) algorithm, as well as statistical considerations that yield new insights into the accuracy with which the relative orientations of individual particles may be determined. A so-called gold-standard Fourier shell correlation (FSC) procedure to prevent overfitting is also described. The resulting implementation yields high-quality reconstructions and reliable resolution estimates with minimal user intervention and at acceptable computational costs.
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        EMAN2: an extensible image processing suite for electron microscopy.

        EMAN is a scientific image processing package with a particular focus on single particle reconstruction from transmission electron microscopy (TEM) images. It was first released in 1999, and new versions have been released typically 2-3 times each year since that time. EMAN2 has been under development for the last two years, with a completely refactored image processing library, and a wide range of features to make it much more flexible and extensible than EMAN1. The user-level programs are better documented, more straightforward to use, and written in the Python scripting language, so advanced users can modify the programs' behavior without any recompilation. A completely rewritten 3D transformation class simplifies translation between Euler angle standards and symmetry conventions. The core C++ library has over 500 functions for image processing and associated tasks, and it is modular with introspection capabilities, so programmers can add new algorithms with minimal effort and programs can incorporate new capabilities automatically. Finally, a flexible new parallelism system has been designed to address the shortcomings in the rigid system in EMAN1.
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          SPIDER and WEB: processing and visualization of images in 3D electron microscopy and related fields.

          The SPIDER system has evolved into a comprehensive tool set for image processing, making use of modern graphics interfacing in the VMS and UNIX environment. SPIDER and WEB handle the complementary tasks of batch processing and visualization of the results. The emphasis of the SPIDER system remains in the area of single particle averaging and reconstruction, although a variety of other application areas have been added. Novel features are a suite of operations relating to the determination, modeling, and correction of the contrast transfer function and the availability of the entire documentation in hypertext format.

            Author and article information

            MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, CB2 0QH Cambridge, UK
            Author notes
            [* ]Corresponding author. scheres@
            J Struct Biol
            J. Struct. Biol
            Journal of Structural Biology
            Academic Press
            1 June 2017
            June 2017
            : 198
            : 3
            : 163-176
            © 2017 MRC Laboratory of Molecular Biology

            This is an open access article under the CC BY license (



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