CSpace  > 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, Yongchun1,2,3; Zeng, Xiangrui4; Zhao, Xiaofang1,2; Li, Shirui2,3; Li, Hua1,2,3; Gao, Xin5; Xu, Min4
2019-08-28
发表期刊BMC BIOINFORMATICS
ISSN1471-2105
卷号20期号:1页码:13
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.
关键词Stochastic average gradient Fine-grained alignment Cryo-ET MPI
DOI10.1186/s12859-019-3003-2
收录类别SCI
语种英语
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
WOS类目Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology
WOS记录号WOS:000483348400001
出版者BMC
引用统计
被引频次:6[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/4741
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.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
4.Carnegie Mellon Univ, Sch Comp Sci, Computat Biol Dept, Pittsburgh, PA 15213 USA
5.KAUST, CBRC, Comp Elect & Math Sci & Engn CEMSE Div, Thuwal, Saudi Arabia
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.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Lu, Yongchun]的文章
[Zeng, Xiangrui]的文章
[Zhao, Xiaofang]的文章
百度学术
百度学术中相似的文章
[Lu, Yongchun]的文章
[Zeng, Xiangrui]的文章
[Zhao, Xiaofang]的文章
必应学术
必应学术中相似的文章
[Lu, Yongchun]的文章
[Zeng, Xiangrui]的文章
[Zhao, Xiaofang]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。