Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review

doi:10.1109/TNNLS.2021.3131325

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review
	Wu, Jia-Geng 4; Yan, Yang 4; Zhang, Dong-Xu 4; Liu, Bo-Wen 4; Zheng, Qing-Bing 4; Xie, Xiao-Liang 3; Liu, Shi-Qi 3; Ge, Sheng-Xiang 4; Hou, Zeng-Guang 1,2,3; Xia, Ning-Shao 5,6
刊名	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2022-02-01
卷号	33 期号:2 页码:452-472
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)
ISSN号	2162-237X
DOI	10.1109/TNNLS.2021.3131325
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)
英文摘要	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.
资助项目	National Natural Science Foundation of China[62003284]
WOS关键词	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
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000752016400005
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/47364]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Zhang, Dong-Xu; Hou, Zeng-Guang; Xia, Ning-Shao
作者单位	1.CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Xiamen Univ, Sch Publ Hlth, State Key Lab Mol Vaccinol & Mol Diagnost, Xiamen 361102, Peoples R China 5.Chinese Acad Med Sci, Res Unit Frontier Technol Struct Vaccinol, Xiamen 361102, Peoples R China 6.Xiamen Univ, State Key Lab Mol Vaccinol & Mol Diagnost, Natl Inst Diagnost & Vaccine Dev Infect Dis, Sch Publ Hlth, Xiamen 361102, Peoples R China
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.