AuTom: a novel automatic platform for electron tomography reconstruction

Handle URI:
http://hdl.handle.net/10754/625269
Title:
AuTom: a novel automatic platform for electron tomography reconstruction
Authors:
Han, Renmin; Wan, Xiaohua; Wang, Zihao; Hao, Yu; Zhang, Jingrong; Chen, Yu; Gao, Xin ( 0000-0002-7108-3574 ) ; Liu, Zhiyong; Ren, Fei; Sun, Fei; Zhang, Fa
Abstract:
We have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the “missing wedge” effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Han R, Wan X, Wang Z, Hao Y, Zhang J, et al. (2017) AuTom: a novel automatic platform for electron tomography reconstruction. Journal of Structural Biology. Available: http://dx.doi.org/10.1016/j.jsb.2017.07.008.
Publisher:
Elsevier BV
Journal:
Journal of Structural Biology
Issue Date:
26-Jul-2017
DOI:
10.1016/j.jsb.2017.07.008
Type:
Article
ISSN:
1047-8477
Sponsors:
Thanks Jose-Jesus Fernandez for opening the CTF module to us. Thanks Ce Liu and Shuangbo Zhang for the works to improve the quality of AuTom. This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No.XDB08030202), the National Natural Science Foundation of China (Grant No. 61232001, 61232991, 61472397, 61502455, 61672493, U1611263, U1611261), the National Key Research and Development Program of China2017YFA0504702), the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Awards No. URF/1/1976-04, URF/1/2602-01, and URF/1/3007-01, Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase), and the National Basic Research Program (973 Program) of Ministry of Science and Technology of China (2014CB910700).
Additional Links:
http://www.sciencedirect.com/science/article/pii/S1047847717301284
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHan, Renminen
dc.contributor.authorWan, Xiaohuaen
dc.contributor.authorWang, Zihaoen
dc.contributor.authorHao, Yuen
dc.contributor.authorZhang, Jingrongen
dc.contributor.authorChen, Yuen
dc.contributor.authorGao, Xinen
dc.contributor.authorLiu, Zhiyongen
dc.contributor.authorRen, Feien
dc.contributor.authorSun, Feien
dc.contributor.authorZhang, Faen
dc.date.accessioned2017-07-27T11:21:47Z-
dc.date.available2017-07-27T11:21:47Z-
dc.date.issued2017-07-26en
dc.identifier.citationHan R, Wan X, Wang Z, Hao Y, Zhang J, et al. (2017) AuTom: a novel automatic platform for electron tomography reconstruction. Journal of Structural Biology. Available: http://dx.doi.org/10.1016/j.jsb.2017.07.008.en
dc.identifier.issn1047-8477en
dc.identifier.doi10.1016/j.jsb.2017.07.008en
dc.identifier.urihttp://hdl.handle.net/10754/625269-
dc.description.abstractWe have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the “missing wedge” effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.en
dc.description.sponsorshipThanks Jose-Jesus Fernandez for opening the CTF module to us. Thanks Ce Liu and Shuangbo Zhang for the works to improve the quality of AuTom. This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No.XDB08030202), the National Natural Science Foundation of China (Grant No. 61232001, 61232991, 61472397, 61502455, 61672493, U1611263, U1611261), the National Key Research and Development Program of China2017YFA0504702), the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Awards No. URF/1/1976-04, URF/1/2602-01, and URF/1/3007-01, Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase), and the National Basic Research Program (973 Program) of Ministry of Science and Technology of China (2014CB910700).en
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S1047847717301284en
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Journal of Structural Biology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Structural Biology, [, , (2017-07-26)] DOI: 10.1016/j.jsb.2017.07.008 . © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectElectron tomographyen
dc.subjectAlignmenten
dc.subjectReconstructionen
dc.subjectImage processing workflowen
dc.titleAuTom: a novel automatic platform for electron tomography reconstructionen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalJournal of Structural Biologyen
dc.eprint.versionPost-printen
dc.contributor.institutionKey Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, Chinaen
dc.contributor.institutionUniversity of Chinese Academy of Sciences, Beijing, Chinaen
dc.contributor.institutionState Key Lab for Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, Chinaen
dc.contributor.institutionCenter for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, Chinaen
dc.contributor.institutionNational Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, Chinaen
kaust.authorHan, Renminen
kaust.authorGao, Xinen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.