Document Detail


TMaCS: A hybrid template matching and classification system for partially-automated particle selection.
MedLine Citation:
PMID:  23333657     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Selection of particle images from electron micrographs presents a bottleneck in determining the structures of macromolecular assemblies by single particle electron cryomicroscopy (cryo-EM). The problem is particularly important when an experimentalist wants to improve the resolution of a 3D map by increasing by tens or hundreds or thousands of images the size of the dataset used for calculating the map. Although several existing methods for automatic particle image selection work well for large protein complexes that produce high-contrast images, it is well known in the cryo-EM community that small complexes that give low-contrast images are often refractory to existing automated particle image selection schemes. Here we develop a method for partially-automated particle image selection when an initial 3D map of the protein under investigation is already available. Candidate particle images are selected from micrographs by template matching with template images derived from projections of the existing 3D map. The candidate particle images are then used to train a support vector machine, which classifies the candidates as particle images or non-particle images. In a final step in the analysis, the selected particle images are subjected to projection matching against the initial 3D map, with the correlation coefficient between the particle image and the best matching map projection used to assess the reliability of the particle image. We show that this approach is able to rapidly select particle images from micrographs of a rotary ATPase, a type of membrane protein complex involved in many aspects of biology.
Authors:
Jianhua Zhao; Marcus A Brubaker; John L Rubinstein
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-16
Journal Detail:
Title:  Journal of structural biology     Volume:  -     ISSN:  1095-8657     ISO Abbreviation:  J. Struct. Biol.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-21     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9011206     Medline TA:  J Struct Biol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2013. Published by Elsevier Inc.
Affiliation:
Molecular Structure and Function Program, The Hospital for Sick Children Research Institute; Department of Medical Biophysics, University of Toronto.
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