Fast maximum-likelihood refinement of electron microscopy images

被引：54

作者：

Scheres, SHW ^{[1
]}

Valle, M ^{[1
]}

Carazo, JM ^{[1
]}

机构：

[1] CSIC, Ctr Nacl Biotecnol, E-28049 Madrid, Spain

来源：

BIOINFORMATICS | 2005年 / 21卷

基金：

美国国家卫生研究院;

关键词：

D O I：

10.1093/bioinformatics/bti1140

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: Maximum-likelihood (ML) image refinement is a promising candidate to improve attainable resolution limits in 3D-EM. However, its large CPU requirements may prohibit application to 3D-structure optimization. Results: We speeded up ML image refinement by reducing its search space over the alignment parameters. Application of this reduced-search approach to a cryo-EM dataset yielded practically identical results as the original approach, but in approximately one day instead of one week of CPU.

引用

收藏

页码：243 / 244

页数：2

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