Three-Dimensional Electron Microscopy of Macromolecular Assemblies

By Joachim Frank. 2006

929 citations recorded by the source corpus.

Subfields: Structural Biology, Surfaces, Coatings and Films

View Paper: https://www.semanticscholar.org/paper/0614847d75c61298856ec529d960d8a8d250ce7e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Structural Biology

In Surfaces, Coatings and Films

Citations in the corpus

Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization (2007, neutral): “In the single-particle reconstruction approach (see ref”
Electron tomography and holography in materials science. (2009, background): “; (2) single-particle analysis, in which images of the same 'particle' (for example a virus) are recorded at different, often random, orientation”
Q|R: quantum-based refinement. (2017, neutral): “These two methods are rather different from technological and conceptual perspectives (Frank, 2006; Rupp, 2010); however, they both yield a map into which an initial atomic model is built.”
SPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs (2008, neutral): “Image processing follows various mathematical procedure”
Crystal contacts as nature's docking solutions (2010, background): “J Comput Chem 31: 133–143, 2010 Key words: macromolecular crystals; protein–protein interactions; protein–protein docking; crystal misrepresentation effects; failure rate analysis; thermodynamic equilibrium”
3D Variability Analysis: Resolving continuous flexibility and discrete heterogeneity from single particle cryo-EM (2020, methodology): “Under the standard cryo-EM image formation model (Frank, 2007; Grigorieff, 2007; Punjani et al., 2017; Scheres, 2012a), a 2D particle image, Xi, is a corrupted projection of the target 3D density V from an unobserved pose φi, plus additive noise, η.”
Resolution measures in molecular electron microscopy (2010, methodology): “In order to adress the shortcomings of the method described in (Penczek and Frank, 2006) the authors propose to take advantage of inherent, even if only directional, oversampling of 3D Fourier space while using standard ET data collection geometries.”
A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy (2016, methodology): “If the template is based on a 3D model, it is usually not trivial to determine a high-quality initial model from new samples, which involves a complete procedure of the ab initio 3D structure determination at low resolution [1].”
Negative Staining and Image Classification – Powerful Tools in Modern Electron Microscopy (2004, methodology): “A mathematical description of classification algorithms is beyond the scope of this paper and the interested reader is referred to (22) as an excellent introduction to the subject.”
Real-space refinement in PHENIX for cryo-EM and crystallography (2018, background): “In cryo-EM studies real-space refinement is a natural choice because a threedimensional map is the output of the single particle image reconstruction method (Frank, 2006) and does not change in a fundamental way as the atomic model is improved.”
Discovery Through the Computational Microscope (2009, neutral): “…data, as in the case of atomic force microscopy studies (Rief and Grubmüller, 2002; Zlatanova and van Holde, 2006; Sotomayor and Schulten, 2007; Prevost et al., 2009) or the analysis of macromolecular structures using electron microscopy (Saibil, 2000; Frank, 2006; Trabuco et al., 2008).”