A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM

doi:10.1109/TCBB.2015.2415787

	A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM
	Zhang, Fa 1; Chen, Yu 1,2; Ren, Fei 1; Wang, Xuan 3; Liu, Zhiyong 4; Wan, Xiaohua 1
	2017-03-01
发表期刊	IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
ISSN	1545-5963
卷号	14 期号:2 页码:316-325
摘要	Particle selection from cryo-electron microscopy (Cryo-EM) images is very important for high-resolution reconstruction of macromolecular structure. The methods of particle selection can be roughly grouped into two classes, template-matching methods and feature-based methods. In general, template-matching methods usually generate better results than feature-based methods. However, the accuracy of template-matching methods is restricted by the noise and low contrast of Cryo-EM images. Moreover, the processing speed of template-matching methods, restricted by the random orientation of particles, further limits their practical applications. In this paper, combining the advantages of feature-based methods and template-matching methods, we present a two-phase improved correlation method for automatic, fast particle selection. In Phase I, we generate a preliminary particle set using rotation-invariant features of particles. In Phase II, we filter the preliminary particle set using a correlation method to reduce the interference of the high noise background and improve the precision of particle selection. We apply several optimization strategies, including a modified adaboost algorithm, Divide and Conquer technique, cascade strategy and graphics processing unit parallel technique, to improve feature recognition ability and reduce processing time. In addition, we developed two correlation score functions for different correlation situations. Experimental results on the benchmark of Cryo-EM images show that our method can improve the accuracy and processing speed of particle selection significantly.
关键词	Particle selection feature-based template-matching rotation-invariant feature correlation score functions
DOI	10.1109/TCBB.2015.2415787
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61232001] ; National Natural Science Foundation of China[61202210] ; National Natural Science Foundation of China[61103139] ; National Natural Science Foundation of China[61472397] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB08030202]
WOS研究方向	Biochemistry & Molecular Biology ; Computer Science ; Mathematics
WOS类目	Biochemical Research Methods ; Computer Science, Interdisciplinary Applications ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS记录号	WOS:000399013500010
出版者	IEEE COMPUTER SOC
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/7292
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Fa
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Yanshan Univ, Qinhuangdao 066004, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Fa,Chen, Yu,Ren, Fei,et al. A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM[J]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,2017,14(2):316-325.
APA	Zhang, Fa,Chen, Yu,Ren, Fei,Wang, Xuan,Liu, Zhiyong,&Wan, Xiaohua.(2017).A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM.IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,14(2),316-325.
MLA	Zhang, Fa,et al."A Two-Phase Improved Correlation Method for Automatic Particle Selection in Cryo-EM".IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 14.2(2017):316-325.