Big data in cryoEM: automated collection, processing and accessibility of EM data.
Philip R. Baldwin,Yong Zi Tan,Edward T. Eng,William J. Rice,Alex J. Noble,Carl J. Negro,Michael A. Cianfrocco,Clinton S. Potter,Bridget Carragher +8 more
TLDR
A brief survey of the developments leading to the current status is provided, and existing cryoEM pipelines are described, with an emphasis on the scope of data acquisition, methods for automation, and use of cloud storage and computing.About:
This article is published in Current Opinion in Microbiology.The article was published on 2018-06-01 and is currently open access. It has received 48 citations till now.read more
Citations
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Automated map sharpening by maximization of detail and connectivity
Thomas C. Terwilliger,Oleg V. Sobolev,Pavel V. Afonine,Pavel V. Afonine,Paul D. Adams,Paul D. Adams +5 more
TL;DR: A procedure for optimizing the sharpening of a map based on maximizing the level of detail and connectivity of the map has been developed and applied to 361 pairs of deposited cryo-EM maps and associated models.
Journal ArticleDOI
Towards data-driven next-generation transmission electron microscopy.
Steven R. Spurgeon,Colin Ophus,Lewys Jones,Amanda K. Petford-Long,Sergei V. Kalinin,Matthew J. Olszta,Rafal E. Dunin-Borkowski,Norman Salmon,Khalid Hattar,Wei-Chang Yang,Renu Sharma,Yingge Du,Ann N. Chiaramonti,Haimei Zheng,Edgar C. Buck,Libor Kovarik,R. Lee Penn,Dongsheng Li,Xin Zhang,Mitsuhiro Murayama,Mitra L. Taheri +20 more
TL;DR: The open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade is discussed.
Posted ContentDOI
Automated map sharpening by maximization of detail and connectivity
TL;DR: An algorithm for automatic map sharpening that is based on optimization of detail and connectivity of the sharpened map is presented and a simple metric based on map-model correlation is used that can reproduce visual choices of optimally-sharpened maps is used.
Journal ArticleDOI
In‐situ Transmission Electron Microscope Techniques for Heterogeneous Catalysis
TL;DR: In this paper, the authors summarized recent advances in the in-situ transmission electron microscope analysis of heterogeneous catalysis, which suggests the great potential of this technique in this important field.
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APPLE picker: Automatic particle picking, a low-effort cryo-EM framework.
TL;DR: The APPLE (Automatic Particle Picking with Low user effort) picker as discussed by the authors is a simple and novel approach for fast, accurate, and template-free particle picking, which is evaluated on publicly available datasets containing micrographs of β-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.
References
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MotionCor2: Anisotropic Correction of Beam-Induced Motion for Improved Cryo-Electron Microscopy
Shawn Q. Zheng,Eugene Palovcak,Jean Paul Armache,Kliment A. Verba,Yifan Cheng,David A. Agard +5 more
TL;DR: MotionCor2 software corrects for beam-induced sample motion, improving the resolution of cryo-EM reconstructions.
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RELION: implementation of a Bayesian approach to cryo-EM structure determination.
TL;DR: Developments that reduce the computational costs of the underlying maximum a posteriori (MAP) algorithm, as well as statistical considerations that yield new insights into the accuracy with which the relative orientations of individual particles may be determined are described.
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cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
TL;DR: It is shown that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer.
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Automated electron microscope tomography using robust prediction of specimen movements.
TL;DR: A new method was developed to acquire images automatically at a series of specimen tilts, as required for tomographic reconstruction, using changes in specimen position at previous tilt angles to predict the position at the current tilt angle.
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CTFFIND4: Fast and accurate defocus estimation from electron micrographs.
Alexis Rohou,Nikolaus Grigorieff +1 more
TL;DR: Modifications to the CTFFIND algorithm are described which make it significantly faster and more suitable for use with images collected using modern technologies such as dose fractionation and phase plates.