Likelihood-based classification of cryo-EM images using FREALIGN

被引:189
作者
Lyumkis, Dmitry [1 ]
Brilot, Axel F. [2 ]
Theobald, Douglas L. [2 ]
Grigorieff, Nikolaus [2 ,3 ]
机构
[1] Scripps Res Inst, Dept Integrat Struct & Computat Biol, Natl Resource Automated Mol Microscopy, La Jolla, CA 92037 USA
[2] Brandeis Univ, Rosenstiel Basic Med Sci Res Ctr, Dept Biochem, Waltham, MA 02454 USA
[3] Brandeis Univ, Howard Hughes Med Inst, Waltham, MA 02454 USA
基金
加拿大自然科学与工程研究理事会; 美国国家卫生研究院;
关键词
Electron microscopy; Maximum likelihood; Classification; Single particle; Protein structure; PARTICLE ELECTRON-MICROSCOPY; UNIFIED DATA RESOURCE; 3-DIMENSIONAL RECONSTRUCTION; DISORDERED SPECIMENS; SINGLE PARTICLES; REFINEMENT; RIBOSOME; RESOLUTION; CRYOMICROSCOPY; IMPLEMENTATION;
D O I
10.1016/j.jsb.2013.07.005
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
We describe an implementation of maximum likelihood classification for single particle electron cryomicroscopy that is based on the FREALIGN software. Particle alignment parameters are determined by maximizing a joint likelihood that can include hierarchical priors, while classification is performed by expectation maximization of a marginal likelihood. We test the FREALIGN implementation using a simulated dataset containing computer-generated projection images of three different 70S ribosome structures, as well as a publicly available dataset of 70S ribosomes. The results show that the mixed strategy of the new FREALIGN algorithm yields performance on par with other maximum likelihood implementations, while remaining computationally efficient. (c) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:377 / 388
页数:12
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