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AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction

文献类型：期刊论文

作者Zhang, Fa4; Liu, Zhiyong4; Sun, Fei1; Wang, Sheng5; Li, Yu5; Yang, Peng5; Lawrence, Albert2; Li, Lun3,4; Wan, Xiaohua4; Han, Renmin5
刊名BIOINFORMATICS
出版日期2019-01-15
卷号35期号:2页码:319-328
ISSN号1367-4803
DOI10.1093/bioinformatics/bty620
英文摘要Motivation: Dual-axis electron tomography is an important 3D macro-molecular structure reconstruction technology, which can reduce artifacts and suppress the effect of missing wedge. However, the fully automatic data process for dual-axis electron tomography still remains a challenge due to three difficulties: (i) how to track the mass of fiducial markers automatically; (ii) how to integrate the information from the two different tilt series; and (iii) how to cope with the inconsistency between the two different tilt series. Results: Here we develop a toolkit for fully automatic alignment of dual-axis electron tomography, with a simultaneous reconstruction procedure. The proposed toolkit and its workflow carries out the following solutions: (i) fully automatic detection and tracking of fiducial markers under large-field datasets; (ii) automatic combination of two different tilt series and global calibration of projection parameters; and (iii) inconsistency correction based on distortion correction parameters and the consequently simultaneous reconstruction. With all of these features, the presented toolkit can achieve accurate alignment and reconstruction simultaneously and conveniently under a single global coordinate system.
资助项目National Key Research and Development Program of China[2017YFE0103900] ; National Key Research and Development Program of China[2017YFA0504702] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[FCC/1/1976-04] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/2601-01] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/3007-01] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/3412-01] ; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)[URF/1/3450-01] ; National natural Science Foundation of China[U1611263] ; National natural Science Foundation of China[U1611261] ; National natural Science Foundation of China[61472397] ; National natural Science Foundation of China[61502455] ; National natural Science Foundation of China[61672493] ; Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase)
WOS研究方向Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
语种英语
WOS记录号WOS:000459314900017
出版者OXFORD UNIV PRESS
源URL[http://119.78.100.204/handle/2XEOYT63/3406]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhang, Fa; Gao, Xin
作者单位1.Chinese Acad Sci, Inst Biophys, Natl Lab Biomacromol, Beijing 100101, Peoples R China
2.Univ Calif San Diego, Ctr Res Biol Syst, Natl Ctr Microscopy & Imaging Res, San Diego, CA 92093 USA
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, High Performance Comp Res Ctr, Beijing 100190, Peoples R China
5.KAUST, CBRC, Comp Elect & Math Sci & Engn CEMSE Div, Thuwal 239556900, Saudi Arabia
推荐引用方式
GB/T 7714		 Zhang, Fa,Liu, Zhiyong,Sun, Fei,et al. AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction[J]. BIOINFORMATICS,2019,35(2):319-328.
APA Zhang, Fa.,Liu, Zhiyong.,Sun, Fei.,Wang, Sheng.,Li, Yu.,...&Gao, Xin.(2019).AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction.BIOINFORMATICS,35(2),319-328.
MLA Zhang, Fa,et al."AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction".BIOINFORMATICS 35.2(2019):319-328.

入库方式： OAI收割

来源：计算技术研究所

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