Unsupervised Cryo-EM Data Clustering through Adaptively Constrained   K-Means Algorithm

doi:10.1371/journal.pone.0167765

CORC > 北京大学 > 生命科学学院

	Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm
	Xu, Yaofang ; Wu, Jiayi ; Yin, Chang-Cheng ; Mao, Youdong
刊名	PLOS ONE
	2016
关键词	ELECTRON-MICROSCOPY IMAGES SINGLE-PARTICLES BIOLOGICAL MACROMOLECULES ANGSTROM RESOLUTION RECONSTRUCTION PROJECTIONS CLASSIFICATION HETEROGENEITY COMPLEXES SOFTWARE
DOI	10.1371/journal.pone.0167765
英文摘要	In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.; grant of the Thousand Talents Plan of China; National Natural Science Foundation of China [91530321]; Intel Parallel Computing Center program; National Science Foundation under NSF [1541959]; NIH, Center for HIV/AIDS Vaccine Immunology and Immunogen Design (CHAVI-ID) [AI100645]; SCI(E); ARTICLE; ccyin@hsc.pku.edu.cn; youdong_mao@dfci.harvard.edu; 12; 11
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/458062]
专题	生命科学学院
推荐引用方式 GB/T 7714	Xu, Yaofang,Wu, Jiayi,Yin, Chang-Cheng,et al. Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm[J]. PLOS ONE,2016.
APA	Xu, Yaofang,Wu, Jiayi,Yin, Chang-Cheng,&Mao, Youdong.(2016).Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.PLOS ONE.
MLA	Xu, Yaofang,et al."Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm".PLOS ONE (2016).