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How cryo-EM is revolutionizing structural biology
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RELION: Implementation of a Bayesian approach to cryo-EM structure determination
Scheres, S. H. W. (2012) · Journal of Structural Biology · doi:10.1016/j.jsb.2012.09.006 · Cited by 5,446
Self-citationKühlbrandt, W. (2014) · Science · doi:10.1126/science.1251652 · Cited by 1,325
Research works printed but not linked: 89
- Ruska, 1941, Über ein neues bei der bakteriophagen Lyse auftretendes Formelement, Naturwissenschaften, 29, 367, 10.1007/BF01479367 · DOI
- Ruska, 1939, Die Bedeutung der Übermikroskopie für die Virusforschung, Arch. Für Gesamte Virusforsch., 1, 155, 10.1007/BF01243399 · DOI
- Brenner, 1959, A negative staining method for high resolution electron microscopy of viruses, Biochim. Biophys. Acta, 34, 103, 10.1016/0006-3002(59)90237-9 · DOI · Paper page
- Henderson, 1975, Three-dimensional model of purple membrane obtained by electron microscopy, Nature, 257, 28, 10.1038/257028a0 · DOI · Paper page
- Unwin, 1975, Molecular structure determination by electron microscopy of unstained crystalline specimens, J. Mol. Biol., 94, 425, 10.1016/0022-2836(75)90212-0 · DOI · Paper page
- Taylor, 1974, Electron diffraction of frozen, hydrated protein crystals, Science, 186, 1036, 10.1126/science.186.4168.1036 · DOI · Paper page
- Hayward, 1979, Radiation damage of purple membrane at low temperature, Ultramicroscopy, 4, 201, 10.1016/S0304-3991(79)90211-0 · DOI
- Adrian, 1984, Cryo-electron microscopy of viruses, Nature, 308, 32, 10.1038/308032a0 · DOI · Paper page
- Dubochet, 1981, Low temperature electron microscopy, Annu. Rev. Biophys. Bioeng., 10, 133, 10.1146/annurev.bb.10.060181.001025 · DOI
- Dubochet, 1988, Cryo-electron microscopy of vitrified specimens, Q. Rev. Biophys., 21, 129, 10.1017/S0033583500004297 · DOI · Paper page
- Nogales, 1998, Structure of the alpha beta tubulin dimer by electron crystallography, Nature, 391, 199, 10.1038/34465 · DOI · Paper page
- Kühlbrandt, 1994, Atomic model of plant light-harvesting complex by electron crystallography, Nature, 367, 614, 10.1038/367614a0 · DOI · Paper page
- Gonen, 2005, Lipid-protein interactions in double-layered two-dimensional AQP0 crystals, Nature, 438, 633, 10.1038/nature04321 · DOI · Paper page
- Unwin, 2005, Refined structure of the nicotinic acetylcholine receptor at 4A resolution, J. Mol. Biol., 346, 967, 10.1016/j.jmb.2004.12.031 · DOI
- Zhou, 1993, Prospects for using an IVEM with a FEG for imaging macromolecules towards atomic resolution, Ultramicroscopy, 49, 407, 10.1016/0304-3991(93)90246-T · DOI
- Henderson, 1995, The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules, Q. Rev. Biophys., 28, 171, 10.1017/S003358350000305X · DOI · Paper page
- Böttcher, 1997, Determination of the fold of the core protein of hepatitis B virus by electron cryomicroscopy, Nature, 386, 88, 10.1038/386088a0 · DOI · Paper page
- Conway, 1997, Visualization of a 4-helix bundle in the hepatitis B virus capsid by cryo-electron microscopy, Nature, 386, 91, 10.1038/386091a0 · DOI
- Jiang, 2008, Backbone structure of the infectious epsilon15 virus capsid revealed by electron cryomicroscopy, Nature, 451, 1130, 10.1038/nature06665 · DOI
- Yu, 2008, 3.88 A structure of cytoplasmic polyhedrosis virus by cryo-electron microscopy, Nature, 453, 415, 10.1038/nature06893 · DOI · Paper page
- Zhang, 2008, Near-atomic resolution using electron cryomicroscopy and single-particle reconstruction, Proc. Natl. Acad. Sci. U.S.A., 105, 1867, 10.1073/pnas.0711623105 · DOI · Paper page
- Zhang, 2010, 3.3Å cryo-EM structure of a nonenveloped virus reveals a priming mechanism for cell entry, Cell, 141, 472, 10.1016/j.cell.2010.03.041 · DOI · Paper page
- Liu, 2010, Atomic structure of human adenovirus by cryo-EM reveals interactions among protein networks, Science, 329, 1038, 10.1126/science.1187433 · DOI · Paper page
- Verschoor, 1984, Three-dimensional reconstruction of the 30 S ribosomal subunit from randomly oriented particles, J. Mol. Biol., 178, 677, 10.1016/0022-2836(84)90245-6 · DOI
- Radermacher, 1987, Three-dimensional structure of the large ribosomal subunit from Escherichia coli, EMBO J., 6, 1107, 10.1002/j.1460-2075.1987.tb04865.x · DOI
- Frank, 1981, Computer averaging of electron micrographs of 40S ribosomal subunits, Science, 214, 1353, 10.1126/science.7313694 · DOI
- Van Heel, 1981, Use of multivariate statistics in analysing the images of biological macromolecules, Ultramicroscopy, 6, 187
- Harauz, 1986, Exact filters for general geometry three dimensional reconstruction, Optik, 73, 146
- Frank, 1987, On the correction of the contrast transfer function in biological electron microscopy, Optik, 98, 125
- Frank, 1991, Three-dimensional reconstruction of the 70S Escherichia coli ribosome in ice: the distribution of ribosomal RNA, J. Cell Biol., 115, 597, 10.1083/jcb.115.3.597 · DOI
- Gabashvili, 2000, Solution structure of the E. coli 70S ribosome at 11.5Å resolution, Cell, 100, 537, 10.1016/S0092-8674(00)80690-X · DOI · Paper page
- Hamilton, 1967, Image recording in electron microscopy, J. Opt. Soc. Am., 57, 232, 10.1364/JOSA.57.000232 · DOI
- McMullan, 2009, Detective quantum efficiency of electron area detectors in electron microscopy, Ultramicroscopy, 109, 1126, 10.1016/j.ultramic.2009.04.002 · DOI
- Roberts, 1982, A CCD-based image recording system for the CTEM, Ultramicroscopy, 8, 385, 10.1016/0304-3991(82)90061-4 · DOI
- Spence, 1988, Large dynamic range, parallel detection system for electron diffraction and imaging, Rev. Sci. Instrum., 59, 2102, 10.1063/1.1140039 · DOI
- Krivanek, 1993, Applications of slow-scan CCD cameras in transmission electron microscopy, Ultramicroscopy, 49, 95, 10.1016/0304-3991(93)90216-K · DOI
- Faruqi, 1999, Cooled CCD detector with tapered fibre optics for recording electron diffraction patterns, Ultramicroscopy, 75, 235, 10.1016/S0304-3991(98)00056-4 · DOI
- Suloway, 2005, Automated molecular microscopy: the new Leginon system, J. Struct. Biol., 151, 41, 10.1016/j.jsb.2005.03.010 · DOI · Paper page
- Sander, 2005, Advantages of CCD detectors for de novo three-dimensional structure determination in single-particle electron microscopy, J. Struct. Biol., 151, 92, 10.1016/j.jsb.2005.04.004 · DOI
- Booth, 2004, A 9 angstroms single particle reconstruction from CCD captured images on a 200kV electron cryomicroscope, J. Struct. Biol., 147, 116, 10.1016/j.jsb.2004.02.004 · DOI
- Faruqi, 2011, Electronic detectors for electron microscopy, Q. Rev. Biophys., 44, 357, 10.1017/S0033583511000035 · DOI
- Turchetta, 2001, A monolithic active pixel sensor for charged particle tracking and imaging using standard VLSI CMOS technology, Nucl. Instrum. Methods Phys. Res. Sect. Accel. Spectrometers Detect. Assoc. Equip., 458, 677, 10.1016/S0168-9002(00)00893-7 · DOI
- Milazzo, 2005, Active pixel sensor array as a detector for electron microscopy, Ultramicroscopy, 104, 152, 10.1016/j.ultramic.2005.03.006 · DOI
- Faruqi, 2005, Direct single electron detection with a CMOS detector for electron microscopy, Nucl. Instrum. Methods Phys. Res. Sect. Accel. Spectrometers Detect. Assoc. Equip., 546, 170, 10.1016/j.nima.2005.03.023 · DOI
- McMullan, 2009, Experimental observation of the improvement in MTF from backthinning a CMOS direct electron detector, Ultramicroscopy, 109, 1144, 10.1016/j.ultramic.2009.05.005 · DOI
- Ruskin, 2013, Quantitative characterization of electron detectors for transmission electron microscopy, J. Struct. Biol., 184, 385, 10.1016/j.jsb.2013.10.016 · DOI
- McMullan, 2014, Comparison of optimal performance at 300keV of three direct electron detectors for use in low dose electron microscopy, Ultramicroscopy, 147C, 156, 10.1016/j.ultramic.2014.08.002 · DOI
- Bichsel, 1988, Straggling in thin silicon detectors, Rev. Mod. Phys., 60, 663, 10.1103/RevModPhys.60.663 · DOI · Paper page
- McMullan, 2009, Enhanced imaging in low dose electron microscopy using electron counting, Ultramicroscopy, 109, 1411, 10.1016/j.ultramic.2009.07.004 · DOI
- Li, 2013, Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM, Nat. Methods, 10, 584, 10.1038/nmeth.2472 · DOI
- Li, 2013, Influence of electron dose rate on electron counting images recorded with the K2 camera, J. Struct. Biol., 184, 251, 10.1016/j.jsb.2013.08.005 · DOI
- Gao, 2004, Dynamics of EF-G interaction with the ribosome explored by classification of a heterogeneous cryo-EM dataset, J. Struct. Biol., 147, 283, 10.1016/j.jsb.2004.02.008 · DOI
- Valle, 2002, Cryo-EM reveals an active role for aminoacyl-tRNA in the accommodation process, EMBO J., 21, 3557, 10.1093/emboj/cdf326 · DOI · Paper page
- Sigworth, 1998, A maximum-likelihood approach to single-particle image refinement, J. Struct. Biol., 122, 328, 10.1006/jsbi.1998.4014 · DOI · Paper page
- Scheres, 2007, Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization, Nat. Methods, 4, 27, 10.1038/nmeth992 · DOI · Paper page
- Elad, 2008, Detection and separation of heterogeneity in molecular complexes by statistical analysis of their two-dimensional projections, J. Struct. Biol., 162, 108, 10.1016/j.jsb.2007.11.007 · DOI
- Zhang, 2008, Heterogeneity of large macromolecular complexes revealed by 3D cryo-EM variance analysis, Structure, 16, 1770, 10.1016/j.str.2008.10.011 · DOI
- Spahn, 2009, Exploring conformational modes of macromolecular assemblies by multiparticle cryo-EM, Curr. Opin. Struct. Biol., 19, 623, 10.1016/j.sbi.2009.08.001 · DOI
- Lyumkis, 2013, Likelihood-based classification of cryo-EM images using FREALIGN, J. Struct. Biol., 183, 377, 10.1016/j.jsb.2013.07.005 · DOI · Paper page
- Scheres, 2012, A Bayesian view on cryo-EM structure determination, J. Mol. Biol., 415, 406, 10.1016/j.jmb.2011.11.010 · DOI · Paper page
- Brilot, 2012, Beam-induced motion of vitrified specimen on holey carbon film, J. Struct. Biol., 177, 630, 10.1016/j.jsb.2012.02.003 · DOI · Paper page
- Campbell, 2012, Movies of ice-embedded particles enhance resolution in electron cryo-microscopy, Structure, 20, 1823, 10.1016/j.str.2012.08.026 · DOI · Paper page
- Bai, 2013, Ribosome structures to near-atomic resolution from thirty thousand cryo-EM particles, Elife, 2, e00461, 10.7554/eLife.00461 · DOI · Paper page
- Cao, 2013, TRPV1 structures in distinct conformations reveal activation mechanisms, Nature, 504, 113, 10.1038/nature12823 · DOI · Paper page
- Liao, 2013, Structure of the TRPV1 ion channel determined by electron cryo-microscopy, Nature, 504, 107, 10.1038/nature12822 · DOI
- Allegretti, 2014, Atomic model of the F420-reducing [NiFe] hydrogenase by electron cryo-microscopy using a direct electron detector, Elife, 3, e01963, 10.7554/eLife.01963 · DOI
- Amunts, 2014, Structure of the yeast mitochondrial large ribosomal subunit, Science, 343, 1485, 10.1126/science.1249410 · DOI · Paper page
- Emsley, 2010, Features and development of Coot, Acta Crystallogr. D: Biol. Crystallogr., 66, 486, 10.1107/S0907444910007493 · DOI · Paper page
- Murshudov, 1997, Refinement of macromolecular structures by the maximum-likelihood method, Acta Crystallogr. Sect. D, 53, 240, 10.1107/S0907444996012255 · DOI · Paper page
- DiMaio, 2013, Cryo-EM model validation using independent map reconstructions, Protein Sci., 22, 865, 10.1002/pro.2267 · DOI · Paper page
- Falkner, 2013, Cross-validation in cryo-EM-based structural modeling, Proc. Natl. Acad. Sci. U.S.A., 110, 8930, 10.1073/pnas.1119041110 · DOI
- Wong, 2014, Cryo-EM structure of the Plasmodium falciparum 80S ribosome bound to the anti-protozoan drug emetine, Elife, 10.7554/eLife.03080 · DOI · Paper page
- Lu, 2014, Three-dimensional structure of human γ-secretase, Nature, 512, 166, 10.1038/nature13567 · DOI · Paper page
- Scheres, 2014, Beam-induced motion correction for sub-megadalton cryo-EM particles, Elife, 3, e03665, 10.7554/eLife.03665 · DOI · Paper page
- Fernández, 2013, Molecular architecture of a eukaryotic translational initiation complex, Science, 342, 1240585, 10.1126/science.1240585 · DOI
- Koh, 2014, Taura syndrome virus IRES initiates translation by binding its tRNA-mRNA-like structural element in the ribosomal decoding center, Proc. Natl. Acad. Sci. U.S.A., 111, 9139, 10.1073/pnas.1406335111 · DOI
- Fernández, 2014, Initiation of translation by cricket paralysis virus IRES requires its translocation in the ribosome, Cell, 157, 823, 10.1016/j.cell.2014.04.015 · DOI
- Stark, 1996, Electron radiation damage to protein crystals of bacteriorhodopsin at different temperatures, Ultramicroscopy, 63, 75, 10.1016/0304-3991(96)00045-9 · DOI
- Sader, 2013, Cryomicroscopy of radiation sensitive specimens on unmodified graphene sheets: reduction of electron-optical effects of charging, J. Struct. Biol., 183, 531, 10.1016/j.jsb.2013.04.014 · DOI
- Russo, 2014, Controlling protein adsorption on graphene for cryo-EM using low-energy hydrogen plasmas, Nat. Methods, 11, 649, 10.1038/nmeth.2931 · DOI
- Marr, 2014, Fabrication of carbon films with ∼500nm holes for cryo-EM with a direct detector device, J. Struct. Biol., 185, 42, 10.1016/j.jsb.2013.11.002 · DOI
- Berriman, 2012, Paraxial charge compensator for electron cryomicroscopy, Ultramicroscopy, 116, 106, 10.1016/j.ultramic.2012.03.006 · DOI
- Grigorieff, 2007, FREALIGN: high-resolution refinement of single particle structures, J. Struct. Biol., 157, 117, 10.1016/j.jsb.2006.05.004 · DOI · Paper page
- Ludtke, 1999, EMAN: semiautomated software for high-resolution single-particle reconstructions, J. Struct. Biol., 128, 82, 10.1006/jsbi.1999.4174 · DOI
- Liu, 2007, Averaging tens to hundreds of icosahedral particle images to resolve protein secondary structure elements using a Multi-Path Simulated Annealing optimization algorithm, J. Struct. Biol., 160, 11, 10.1016/j.jsb.2007.06.009 · DOI
- Kostyuchenko, 2014, Near-atomic resolution cryo-electron microscopic structure of dengue serotype 4 virus, J. Virol., 88, 477, 10.1128/JVI.02641-13 · DOI
- Veesler, 2013, Atomic structure of the 75MDa extremophile Sulfolobus turreted icosahedral virus determined by CryoEM and X-ray crystallography, Proc. Natl. Acad. Sci. U.S.A., 110, 5504, 10.1073/pnas.1300601110 · DOI
- Van Heel, 1996, A new generation of the IMAGIC image processing system, J. Struct. Biol., 116, 17, 10.1006/jsbi.1996.0004 · DOI · Paper page
- Greber, 2013, Architecture of the large subunit of the mammalian mitochondrial ribosome, Nature, 505, 515, 10.1038/nature12890 · DOI
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Metadata
- Authors
- Bai, X.-C., McMullan, G., & Scheres, S. H. W.
- Venue
- Trends in Biochemical Sciences
- Publisher
- Elsevier BV
- Published
- 2015-01
- Volume
- 40
- Issue
- 1
- Pages
- 49-57
- ISSN
- 0968-0004 (ISSN-L)
- OpenAlex
- W2072404529
- Cited by
- 936
- References
- 2
- FWCI
- 4.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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