A review of automatic particle recognition in Cryo-EM images

Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles inclu...

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Veröffentlicht in:Sheng wu yi xue gong cheng xue za zhi Jg. 27; H. 5; S. 1178
Hauptverfasser: Wu, Xiaorong, Wu, Xiaoming
Format: Journal Article
Sprache:Chinesisch
Veröffentlicht: China 01.10.2010
Schlagworte:
Animals
Automatic Data Processing
Cryoelectron Microscopy - instrumentation
Cryoelectron Microscopy - methods
Cryoelectron Microscopy - trends
Humans
Image Processing, Computer-Assisted - methods
Imaging, Three-Dimensional
Macromolecular Substances - ultrastructure
Molecular Conformation
Particle Size
Ribosomes - chemistry
Ribosomes - ultrastructure
ISSN:1001-5515
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Zusammenfassung:Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles included in performing reconstructions. Manual selection of particles, even assisted by computer, is a bottleneck of single-particle reconstruction. Cryo-EM image has low signal-to-noise ratio and low contrast, which leads to difficulty in particle picking. Various approaches have been developed to address the problem of automatic particle. This paper describes the application of template-based method, edge based method, feature-based method, neural network, DoG-based and simulated annealing approach in particle picking. The characteristics of various approaches are discussed, and the future development is presented.
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ISSN:1001-5515