AuTom: a novel automatic platform for electron tomography reconstruction
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/625269
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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.
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.
SponsorsThanks 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).
JournalJournal of Structural Biology
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