Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization

doi:10.1186/s12859-019-3003-2

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization
	Lu, Yongchun 1,4,5; Zeng, Xiangrui 3; Zhao, Xiaofang 1,5; Li, Shirui 4,5; Li, Hua 1,4,5; Gao, Xin 2; Xu, Min 3
刊名	BMC BIOINFORMATICS
	2019-08-28
卷号	20 期号:1 页码:13
关键词	Stochastic average gradient Fine-grained alignment Cryo-ET MPI
ISSN号	1471-2105
DOI	10.1186/s12859-019-3003-2
英文摘要	BackgroundCryo-electron tomography (Cryo-ET) is an imaging technique used to generate three-dimensional structures of cellular macromolecule complexes in their native environment. Due to developing cryo-electron microscopy technology, the image quality of three-dimensional reconstruction of cryo-electron tomography has greatly improved.However, cryo-ET images are characterized by low resolution, partial data loss and low signal-to-noise ratio (SNR). In order to tackle these challenges and improve resolution, a large number of subtomograms containing the same structure needs to be aligned and averaged. Existing methods for refining and aligning subtomograms are still highly time-consuming, requiring many computationally intensive processing steps (i.e. the rotations and translations of subtomograms in three-dimensional space).ResultsIn this article, we propose a Stochastic Average Gradient (SAG) fine-grained alignment method for optimizing the sum of dissimilarity measure in real space. We introduce a Message Passing Interface (MPI) parallel programming model in order to explore further speedup.ConclusionsWe compare our stochastic average gradient fine-grained alignment algorithm with two baseline methods, high-precision alignment and fast alignment. Our SAG fine-grained alignment algorithm is much faster than the two baseline methods. Results on simulated data of GroEL from the Protein Data Bank (PDB ID:1KP8) showed that our parallel SAG-based fine-grained alignment method could achieve close-to-optimal rigid transformations with higher precision than both high-precision alignment and fast alignment at a low SNR (SNR=0.003) with tilt angle range +/- 60 degrees or +/- 40 degrees. For the experimental subtomograms data structures of GroEL and GroEL/GroES complexes, our parallel SAG-based fine-grained alignment can achieve higher precision and fewer iterations to converge than the two baseline methods.
资助项目	King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/2602-01] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/3007-01] ; National Key R&D Program of China[2017YFB1002703] ; Key Research Program of Frontier Science of Chinese Academy of Sciences[QYZDB-SSW-SMC004] ; U.S. National Institutes of Health (NIH)[P41 GM103712] ; Samuel and Emma Winters Foundation ; Carnegie Mellon University's Center for Machine Learning and Health
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
语种	英语
出版者	BMC
WOS记录号	WOS:000483348400001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/4740]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Lu, Yongchun; Xu, Min
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.KAUST, CBRC, Comp Elect & Math Sci & Engn CEMSE Div, Thuwal, Saudi Arabia 3.Carnegie Mellon Univ, Sch Comp Sci, Computat Biol Dept, Pittsburgh, PA 15213 USA 4.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Lu, Yongchun,Zeng, Xiangrui,Zhao, Xiaofang,et al. Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization[J]. BMC BIOINFORMATICS,2019,20(1):13.
APA	Lu, Yongchun.,Zeng, Xiangrui.,Zhao, Xiaofang.,Li, Shirui.,Li, Hua.,...&Xu, Min.(2019).Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization.BMC BIOINFORMATICS,20(1),13.
MLA	Lu, Yongchun,et al."Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization".BMC BIOINFORMATICS 20.1(2019):13.