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

文献类型：期刊论文

作者Zhang, Fa1; Chen, Yu1,2; Ren, Fei1; Wang, Xuan3; Liu, Zhiyong4; Wan, Xiaohua1
刊名IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
出版日期2017-03-01
卷号14期号:2页码:316-325
关键词Particle selection feature-based template-matching rotation-invariant feature correlation score functions
ISSN号1545-5963
DOI10.1109/TCBB.2015.2415787
英文摘要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.
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
语种英语
WOS记录号WOS:000399013500010
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/7291]  
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.

入库方式： OAI收割

来源：计算技术研究所

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