Abstract
A central task in recovering the structure of a macromolecule using cryo-electron microscopy is to determine a three-dimensional model of the macromolecule from many of its two-dimensional projection images, taken from random and unknown directions. We have recently proposed the globally consistent angular reconstitution (GCAR) [7], which allows to determine a three-dimensional model of the molecule without assuming any prior knowledge on the reconstructed molecule or the distribution of its viewing directions. In this chapter we briefly introduce the idea behind the algorithm [7], and describe several improvements and implementation details required in order to apply it on experimental data. In particular, we extend GCAR with self-stabilizing refinement iterations that increase its robustness to noise, modify the common lines detection procedure to handle the relative (unknown) shifts between images, and demonstrate the algorithm on real data obtained by an electron microscope.
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Acknowledgments
We would like to thank Fred Sigworth and Ronald Coifman for introducing us to the cryo-EM problem and for many stimulating discussions. We also thank Tom Vogt and Wolfgang Dahmen for their hospitality at the Industrial Mathematics Institute and the NanoCenter at the University of South Carolina during “Imaging in Electron Microscopy 2009”. The project described was supported by Award Number R01GM090200 from the National Institute of General Medical Sciences. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health.
Molecular graphics images were produced using the UCSF Chimera package from the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco (supported by NIH P41 RR-01081).
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Singer, A., Shkolnisky, Y. (2012). Center of Mass Operators for Cryo-EM—Theory and Implementation. In: Vogt, T., Dahmen, W., Binev, P. (eds) Modeling Nanoscale Imaging in Electron Microscopy. Nanostructure Science and Technology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2191-7_6
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DOI: https://doi.org/10.1007/978-1-4614-2191-7_6
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