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Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review
Wu, Jia-Geng1; Yan, Yang1; Zhang, Dong-Xu1; Liu, Bo-Wen1; Zheng, Qing-Bing1; Xie, Xiao-Liang2; Liu, Shi-Qi2; Ge, Sheng-Xiang1; Hou, Zeng-Guang2,3,4; Xia, Ning-Shao5,6
发表期刊IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
ISSN2162-237X
2022-02-01
卷号33期号:2页码:452-472
通讯作者Zhang, Dong-Xu(zhangdongxu@xmu.edu.cn) ; Hou, Zeng-Guang(zengguang.hou@ia.ac.cn) ; Xia, Ning-Shao(nsxia@xmu.edu.cn)
摘要Recently, single-particle cryo-electron microscopy (cryo-EM) has become an indispensable method for determining macromolecular structures at high resolution to deeply explore the relevant molecular mechanism. Its recent breakthrough is mainly because of the rapid advances in hardware and image processing algorithms, especially machine learning. As an essential support of single-particle cryo-EM, machine learning has powered many aspects of structure determination and greatly promoted its development. In this article, we provide a systematic review of the applications of machine learning in this field. Our review begins with a brief introduction of single-particle cryo-EM, followed by the specific tasks and challenges of its image processing. Then, focusing on the workflow of structure determination, we describe relevant machine learning algorithms and applications at different steps, including particle picking, 2-D clustering, 3-D reconstruction, and other steps. As different tasks exhibit distinct characteristics, we introduce the evaluation metrics for each task and summarize their dynamics of technology development. Finally, we discuss the open issues and potential trends in this promising field.
关键词Machine learning Periodic structures Task analysis Proteins Photomicrography Coronaviruses Machine learning algorithms Clustering deep learning (DL) image processing machine learning neural network (NN) single-particle cryo-electron microscopy (cryo-EM)
DOI10.1109/TNNLS.2021.3131325
关键词[WOS]CRYO-EM STRUCTURE ; SECONDARY STRUCTURE ELEMENTS ; 3-DIMENSIONAL ELECTRON-MICROSCOPY ; LIKELIHOOD-BASED CLASSIFICATION ; MAXIMUM-LIKELIHOOD ; BIOLOGICAL MACROMOLECULES ; NEURAL-NETWORK ; AUTOMATIC CLASSIFICATION ; CONFORMATIONAL STATES ; 3D RECONSTRUCTION
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[62003284]
项目资助者National Natural Science Foundation of China
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000752016400005
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类多模态智能
引用统计
被引频次:5[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/47365
专题复杂系统认知与决策实验室_先进机器人
通讯作者Zhang, Dong-Xu; Hou, Zeng-Guang; Xia, Ning-Shao
作者单位1.Xiamen Univ, Sch Publ Hlth, State Key Lab Mol Vaccinol & Mol Diagnost, Xiamen 361102, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
5.Xiamen Univ, State Key Lab Mol Vaccinol & Mol Diagnost, Natl Inst Diagnost & Vaccine Dev Infect Dis, Sch Publ Hlth, Xiamen 361102, Peoples R China
6.Chinese Acad Med Sci, Res Unit Frontier Technol Struct Vaccinol, Xiamen 361102, Peoples R China
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Wu, Jia-Geng,Yan, Yang,Zhang, Dong-Xu,et al. Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2022,33(2):452-472.
APA Wu, Jia-Geng.,Yan, Yang.,Zhang, Dong-Xu.,Liu, Bo-Wen.,Zheng, Qing-Bing.,...&Xia, Ning-Shao.(2022).Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,33(2),452-472.
MLA Wu, Jia-Geng,et al."Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 33.2(2022):452-472.
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