| Literature DB >> 24607413 |
Robert Langlois1, Jesper Pallesen2, Jordan T Ash3, Danny Nam Ho4, John L Rubinstein5, Joachim Frank6.
Abstract
Cryo-electron microscopy is an increasingly popular tool for studying the structure and dynamics of biological macromolecules at high resolution. A crucial step in automating single-particle reconstruction of a biological sample is the selection of particle images from a micrograph. We present a novel algorithm for selecting particle images in low-contrast conditions; it proves more effective than the human eye on close-to-focus micrographs, yielding improved or comparable resolution in reconstructions of two macromolecular complexes.Entities:
Keywords: Automation; Cryo-EM; High-resolution; Machine-learning; Particle selection
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Year: 2014 PMID: 24607413 PMCID: PMC4063204 DOI: 10.1016/j.jsb.2014.03.001
Source DB: PubMed Journal: J Struct Biol ISSN: 1047-8477 Impact factor: 2.867