DIALS_for_ED.bib

@book{Arndt1977,
  address = {Amsterdam},
  author = {Arndt, U W and Wonacott, A J},
  pages = {195--202},
  title = {{The rotation method in crystallography}},
  year = {1977},
  publisher = {North-Holland Publishing Company}
}

@inbook{Bernstein2005,
  abstract = {The Crystallographic Binary File (CBF) is an electronic file supporting the efficient storage of large quantities of experimental data in a self-describing binary format. Its primary function is to handle large image data sets within laboratories and for interchange between collaborating groups. Except for embedded binary data segments, the format is derived from that of the pure-ASCII Crystallographic Information File (CIF), so that all suitable CIF data items describing the crystallographic experiment and description of any structural results may be included. Embedding of binary data fields makes use of Internet standard MIME headers to facilitate the identification and handling of separate binary components. Where file size or efficiency of processing are not important, the embedded binary data may be ASCII-encoded according to a specified protocol. The resultant file, containing only ASCII character data, is fully compatible with CIF and is known as an image-supporting crystallographic information file (imgCIF). This chapter describes in detail the structure and format of CBF and imgCIF representations, and explains how to convert from one format to the other. This chapter is also available as HTML from the International Tables Online site hosted by the IUCr.},
  address = {Dordrecht},
  author = {Bernstein, H J and Hammersley, A P},
  booktitle = {International Tables for Crystallography Volume G: Definition and exchange of crystallographic data},
  doi = {10.1107/97809553602060000729},
  editor = {Hall, S R and McMahon, B},
  isbn = {978-1-4020-4290-4},
  pages = {37--43},
  publisher = {Springer Netherlands},
  title = {{Specification of the Crystallographic Binary File (CBF/imgCIF)}},
  url = {https://doi.org/10.1107/97809553602060000729},
  year = {2005}
}

@article{Brunger1997,
author = {Brunger, Axel T.},
file = {:Users/cmax/Dropbox/Literature/brunger1997.pdf:pdf},
journal = {Methods in Enzymology},
pages = {366--396},
title = {{Free R Value: Cross-Validation in Crystallography}},
volume = {277},
year = {1997}
}

@article{Clabbers2017,
  abstract = {Three-dimensional nanometre-sized crystals of
macromolecules currently resist structure elucidation by single-crystal X-ray
crystallography. Here, a single nanocrystal with a diffracting volume of only
0.14 microm3, i.e. no more than 6 x 105 unit cells, provided sufficient
information to determine the structure of a rare dimeric polymorph of hen
egg-white lysozyme by electron crystallography. This is at least an order of
magnitude smaller than was previously possible. The molecular-replacement
solution, based on a monomeric polyalanine model, provided sufficient phasing
power to show side-chain density, and automated model building was used to
reconstruct the side chains. Diffraction data were acquired using the rotation
method with parallel beam diffraction on a Titan Krios transmission electron
microscope equipped with a novel in-house-designed 1024 x 1024 pixel Timepix
hybrid pixel detector for low-dose diffraction data collection. Favourable
detector characteristics include the ability to accurately discriminate single
high-energy electrons from X-rays and count them, fast readout to finely sample
reciprocal space and a high dynamic range. This work, together with other recent
milestones, suggests that electron crystallography can provide an attractive
alternative in determining biological structures.},
 author = {Clabbers, Max T.B.  and van Genderen, E. and Wan, Wei and Wiegers,
 E.L. and Gruene, Tim and Abrahams, Jan Pieter},
 doi = {10.1107/S2059798317010348},
 file = {:home/david/.local/share/data/Mendeley Ltd./Mendeley
Desktop/Downloaded/Clabbers et al. - 2017 - Protein structure determination by
electron diffraction using a single three-dimensional nanocrystal.pdf:pdf},
 isbn = {2059798317010},
 issn = {2059-7983},
 journal = {Acta Cryst. D},
 volume = "73",
 keywords = {0000-0002-8584-9577,article in press,but may be cited,electron crystallography,how to cite your,hybrid pixel detector,numbers,protein nanocrystals,using the doi,yet been assigned page,your article has not},
  mendeley-groups = {electron diffraction},
  pages = {738--748},
  publisher = {International Union of Crystallography},
  title = {{Protein structure determination by electron diffraction using a single three-dimensional nanocrystal}},
 year = {2017}
}

@article{Dauter2015,
  author = "Dauter, Zbigniew and Wlodawer, Alexander",
  title = "{On the accuracy of unit-cell parameters in protein crystallography}",
  journal = "Acta Crystallographica Section D",
  year = "2015",
  volume = "71",
  number = "11",
  pages = "2217--2226",
  month = "Nov",
  doi = {10.1107/S1399004715015503},
  url = {https://doi.org/10.1107/S1399004715015503},
  abstract = {The availability in the Protein Data Bank (PDB) of a number of structures that are presented in space group {\it P}1 but in reality possess higher symmetry allowed the accuracy and precision of the unit-cell parameters of the crystals of macromolecules to be evaluated. In addition, diffraction images from crystals of several proteins, previously collected as part of in-house projects, were processed independently with three popular software packages. An analysis of the results, augmented by published serial crystallography data, suggests that the apparent precision of the presentation of unit-cell parameters in the PDB to three decimal points is not justified, since these parameters are subject to errors of not less than 0.2%. It was also noticed that processing data including full crystallographic symmetry does not lead to deterioration of the refinement parameters; thus, it is not beneficial to treat the crystals as belonging to space group {\it P}1 when higher symmetry can be seen.},
  keywords = {protein crystallography, unit-cell parameter accuracy, symmetry},
}

@article{DelaCruz2017,
  archivePrefix = {arXiv},
  arxivId = {15334406},
  author = {de la Cruz, M Jason and Hattne, Johan and Shi, Dan and Seidler, Paul and Rodriguez, Jose and Reyes, Francis E and Sawaya, Michael R and Cascio, Duilio and Weiss, Simon C and Kim, Sun Kyung and Hinck, Cynthia S and Hinck, Andrew P and Calero, Guillermo and Eisenberg, David and Gonen, Tamir},
  doi = {10.1038/nmeth.4178},
  eprint = {15334406},
  file = {:home/david/Dropbox/references/electron{\_}diffraction/delaCruz2017{\_}atomic{\_}resolution{\_}fragmented.pdf:pdf;:home/david/Dropbox/references/electron{\_}diffraction/delaCruz2017{\_}atomic{\_}resolution{\_}fragmented{\_}suppl.pdf:pdf},
  isbn = {0000000000000},
  issn = {1548-7091},
  journal = {Nature Methods},
  mendeley-groups = {electron diffraction},
  month = {feb},
  number = {4},
  pages = {399--402},
  pmid = {24655651},
  title = {{Atomic-resolution structures from fragmented protein crystals with the cryoEM method MicroED}},
  url = {http://www.nature.com/doifinder/10.1038/nmeth.4178},
  volume = {14},
  year = {2017}
}

@article{Evans2006,
  author = "Evans, Philip",
  title = "{Scaling and assessment of data quality}",
  journal = "Acta Crystallographica Section D",
  year = "2006",
  volume = "62",
  number = "1",
  pages = "72--82",
  month = "Jan",
  doi = {10.1107/S0907444905036693},
  _url = {http://dx.doi.org/10.1107/S0907444905036693},
  abstract = {The various physical factors affecting measured diffraction intensities are discussed, as are the scaling models which may be used to put the data on a consistent scale. After scaling, the intensities can be analysed to set the real resolution of the data set, to detect bad regions ({\it e.g.} bad images), to analyse radiation damage and to assess the overall quality of the data set. The significance of any anomalous signal may be assessed by probability and correlation analysis. The algorithms used by the {\it CCP}4 scaling program {\it SCALA} are described. A requirement for the scaling and merging of intensities is knowledge of the Laue group and point-group symmetries: the possible symmetry of the diffraction pattern may be determined from scores such as correlation coefficients between observations which might be symmetry-related. These scoring functions are implemented in a new program {\it POINTLESS}.},
  keywords = {scaling diffraction data, data quality, Laue group determination},
}

@article{Evans2013,
  author = {Evans, Philip R and Murshudov, Garib N},
  journal = {Acta Crystallogr. D. Biol. Crystallogr.},
  month = {jul},
  number = {Pt 7},
  pages = {1204--14},
  publisher = {International Union of Crystallography},
  title = {{How good are my data and what is the resolution?}},
  volume = {69},
  year = {2013}
}

@article{Foadi2013,
  author = "Foadi, James and Aller, Pierre and Alguel, Yilmaz and Cameron, Alex and Axford, Danny and Owen, Robin L. and Armour, Wes and Waterman, David G. and Iwata, So and Evans, Gwyndaf",
  title = "{Clustering procedures for the optimal selection of data sets from multiple crystals in macromolecular crystallography}",
  journal = "Acta Crystallographica Section D",
  year = "2013",
  volume = "69",
  number = "8",
  pages = "1617--1632",
  month = "Aug",
  doi = {10.1107/S0907444913012274},
  url = {https://doi.org/10.1107/S0907444913012274},
  abstract = {The availability of intense microbeam macromolecular crystallography beamlines at third-generation synchrotron sources has enabled data collection and structure solution from microcrystals of <10{$\mu$}m in size. The increased likelihood of severe radiation damage where microcrystals or particularly sensitive crystals are used forces crystallographers to acquire large numbers of data sets from many crystals of the same protein structure. The associated analysis and merging of multi-crystal data is currently a manual and time-consuming step. Here, a computer program, {\it BLEND}, that has been written to assist with and automate many of the steps in this process is described. It is demonstrated how {\it BLEND} has successfully been used in the solution of a novel membrane protein.},
  keywords = {clustering, multiple crystals, BLEND, scaling, merging, multi-crystal data sets},
}

@article{Gildea2014,
  author = "Gildea, Richard J. and Waterman, David G. and Parkhurst, James M. and Axford, Danny and Sutton, Geoff and Stuart, David I. and Sauter, Nicholas K. and Evans, Gwyndaf and Winter, Graeme",
  title = "{New methods for indexing multi-lattice diffraction data}",
  journal = "Acta Crystallographica Section D",
  year = "2014",
  volume = "70",
  number = "10",
  pages = "2652--2666",
  month = "Oct",
  doi = {10.1107/S1399004714017039},
}

@article{Grosse-Kunstleve2002,
  abstract = {The advent of structural genomics initiatives has led to a pressing need for high-throughput macromolecular structure determination. To accomplish this, new methods and inevitably new software must be developed to accelerate the process of structure solution. To minimize duplication of effort and to generate maintainable code efficiently, a toolbox of basic crystallographic software components is required. The development of the {\{}$\backslash$it Computational Crystallography Toolbox{\}} ({\{}$\backslash$it cctbx{\}}) has been undertaken for this purpose. In this paper, the fundamental requirements for the {\{}$\backslash$it cctbx{\}} are outlined and the decisions that have lead to its implementation are explained. The {\{}$\backslash$it cctbx{\}} currently contains algorithms for the handling of unit cells, space groups and atomic scatterers, and is released under an Open Source license to allow unrestricted use and continued development. It will be developed further to become a comprehensive library of crystallographic tools useful to the entire community of software developers.},
  author = {Grosse-Kunstleve, Ralf W and Sauter, Nicholas K and Moriarty, Nigel W and Adams, Paul D},
  doi = {10.1107/S0021889801017824},
  journal = {Journal of Applied Crystallography},
  keywords = { Human Genome Project, International Tables for Crystallography, object-oriented programming, protein crystallography, structural genomics,macromolecular crystallography},
  month = {feb},
  number = {1},
  pages = {126--136},
  title = {{The {\{}$\backslash$it Computational Crystallography Toolbox{\}}: crystallographic algorithms in a reusable software framework}},
  url = {https://doi.org/10.1107/S0021889801017824},
  volume = {35},
  year = {2002}
}

@article{Gruene2018,
  author = {Gruene, Tim and Li, Teng and van Genderen, Eric and Pinar, Ana B. and van Bokhoven, Jeroen A.},
  title = {Characterization at the Level of Individual Crystals: Single-Crystal MFI Type Zeolite Grains},
  journal = {Chemistry – A European Journal},
  volume = {24},
  number = {10},
  issn = {1521-3765},
  url = {http://dx.doi.org/10.1002/chem.201704213},
  doi = {10.1002/chem.201704213},
  pages = {2384--2388},
  keywords = {electron diffraction, structure–performance relationship, X-ray diffraction, zeolites},
  year = {2018},
}


@article{Hattne2015,
  abstract = {{\textless}p{\textgreater}MicroED, a method at the intersection of X-ray crystallography and electron cryo-microscopy, has rapidly progressed by exploiting advances in both fields and has already been successfully employed to determine the atomic structures of several proteins from sub-micron-sized, three-dimensional crystals. A major limiting factor in X-ray crystallography is the requirement for large and well ordered crystals. By permitting electron diffraction patterns to be collected from much smaller crystals, or even single well ordered domains of large crystals composed of several small mosaic blocks, MicroED has the potential to overcome the limiting size requirement and enable structural studies on difficult-to-crystallize samples. This communication details the steps for sample preparation, data collection and reduction necessary to obtain refined, high-resolution, three-dimensional models by MicroED, and presents some of its unique challenges.{\textless}/p{\textgreater}},
  author = {Hattne, Johan and Reyes, Francis E. and Nannenga, Brent L. and Shi, Dan and {De La Cruz}, M. Jason and Leslie, Andrew G.W. and Gonen, Tamir},
  doi = {10.1107/S2053273315010669},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Hattne2015{\_}microED.pdf:pdf;:home/fcx32934/Documents/Mendeley Desktop/Hattne2015{\_}microED{\_}suppl.pdf:pdf},
  isbn = {2053273315010},
  issn = {20532733},
  journal = {Acta Crystallographica Section A: Foundations and Advances},
  keywords = {MicroED,cryo-EM,crystallography,electron diffraction,nanocrystals},
  mendeley-groups = {electron diffraction},
  pages = {353--360},
  pmid = {26131894},
  publisher = {International Union of Crystallography},
  title = {{MicroED data collection and processing}},
  volume = {71},
  year = {2015}
}


@article{Hattne2016,
  abstract = {The weak pixel counts surrounding the Bragg spots in a diffraction image are important for establishing a model of the background underneath the peak and estimating the reliability of the integrated intensities. Under certain circumstances, particularly with equipment not optimized for low-intensity measurements, these pixel values may be corrupted by corrections applied to the raw image. This can lead to truncation of low pixel counts, resulting in anomalies in the integrated Bragg intensities, such as systematically higher signal-to-noise ratios. A correction for this effect can be approximated by a three-parameter lognormal distribution fitted to the weakly positive-valued pixels at similar scattering angles. The procedure is validated by the improved refinement of an atomic model against structure factor amplitudes derived from corrected micro-electron diffraction (MicroED) images.},
  author = {Hattne, Johan and Shi, Dan and {De La Cruz}, M. Jason and Reyes, Francis E. and Gonen, Tamir},
  doi = {10.1107/S1600576716007196},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Hattne et al. - 2016 - Modeling truncated pixel values of faint reflections in MicroED images.pdf:pdf},
  issn = {16005767},
  journal = {Journal of Applied Crystallography},
  keywords = {CryoEM,Micro-electron diffraction,MicroED,X-ray free-electron lasers,XFELs},
  pages = {1029--1034},
  publisher = {International Union of Crystallography},
  title = {{Modeling truncated pixel values of faint reflections in MicroED images}},
  volume = {49},
  year = {2016}
}

@article{Joosten2014,
abstract = {The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB). The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011), Structure, 19, 1395-1412]. The PDB{\_}REDO procedure aims for `constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB{\_}REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallographers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB{\_}REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.},
author = {Joosten, Robbie P and Long, Fei and Murshudov, Garib N. and Perrakis, Anastassis},
doi = {10.1107/S2052252514009324},
file = {:Users/cmax/Dropbox/Literature/joosten{\_}2014.pdf:pdf},
isbn = {doi:10.1107/S2052252514009324},
issn = {2052-2525},
journal = {IUCrJ},
keywords = {model,pdb{\_}redo,validation},
pages = {213--220},
pmid = {25075342},
publisher = {International Union of Crystallography},
title = {{The PDB{\_}REDO server for macromolecular structure model optimization}},
url = {http://dx.doi.org/10.1107/S2052252514009324},
volume = {1},
year = {2014}
}


@article{kabsch2010xds,
  title={{\mockalph{bbbbb}}XDS},
  author={Kabsch, Wolfgang},
  journal={Acta Crystallographica Section D},
  volume={66},
  number={2},
  pages={125--132},
  year={2010},
  publisher={International Union of Crystallography}
}

@article{Kabsch2010algorithm,
  author = {Kabsch, Wolfgang},
  journal = {Acta Crystallographica Section D},
  month = feb,
  number = {2},
  pages = {133--144},
  publisher = {International Union of Crystallography},
  title = {{\mockalph{ccccc}}Integration, scaling, space-group assignment and post-refinement},
  volume = {66},
  year = {2010}
}

@article{LePage1982,
  abstract = {The identification of twofold axes is straightforward if the cell is based on three of the shortest lattice translations. The distribution of twofold axes in space fixes the lattice symmetry and most conventional cell edges. A program based on this approach has been written. It works for the seven cases with minimum branching of the algorithm.},
  author = {{Le Page}, Y.},
  doi = {10.1107/S0021889882011959},
  file = {:home/david/Dropbox/references/LePage1982{\_}axis{\_}identification.pdf:pdf},
  isbn = {0302550550},
  issn = {0021-8898},
  journal = {Journal of Applied Crystallography},
  number = {3},
  pages = {255--259},
  title = {{The derivation of the axes of the conventional unit cell from the dimensions of the Buerger-reduced cell}},
  volume = {15},
  year = {1982}
}


@article{leslie1999integration,
author = "Leslie, A. G. W.",
title = "{Integration of macromolecular diffraction data}",
journal = "Acta Crystallographica Section D",
year = "1999",
volume = "55",
number = "10",
pages = "1696--1702",
month = "Oct",
doi = {10.1107/S090744499900846X},
}

@article{leslie2006integration,
author = "Leslie, Andrew G. W.",
title = "{The integration of macromolecular diffraction data}",
journal = "Acta Crystallographica Section D",
year = "2006",
volume = "62",
number = "1",
pages = "48--57",
month = "Jan",
doi = {10.1107/S0907444905039107},
}

@incollection{leslie2007,
year={2007},
isbn={978-1-4020-6314-5},
booktitle={Evolving Methods for Macromolecular Crystallography},
volume={245},
series={NATO Science Series},
editor={Read, RandyJ. and Sussman, JoelL.},
doi={10.1007/978-1-4020-6316-9_4},
title={Processing diffraction data with mosflm},
publisher={Springer Netherlands},
author={Leslie, AndrewG.W. and Powell, HaroldR.},
pages={41-51},
language={English}
}

@article{Luebben2015,
abstract = {SignificanceModern crystallographic structure determination uses maximum likelihood methods. They rely on error estimates between the work model and the unknown target based on a small fraction of the data. This can introduce a large uncertainty and, even worse, restricts the method to projects where sufficient data are available. We investigate the Rcomplete method. It enables the use of all data for error estimation. It reduces the uncertainty associated with the conventional Rfree approach for small datasets. We show that our approach reduces the effect of overfitting. This enables maximum likelihood methods to be extended to a much wider field of applications, including free electron laser experiments, high-pressure crystallography, and low-resolution structures. The crystallographic reliability index Rcomplete is based on a method proposed more than two decades ago. Because its calculation is computationally expensive its use did not spread into the crystallographic community in favor of the cross-validation method known as Rfree. The importance of Rfree has grown beyond a pure validation tool. However, its application requires a sufficiently large dataset. In this work we assess the reliability of Rcomplete and we compare it with k-fold cross-validation, bootstrapping, and jackknifing. As opposed to proper cross-validation as realized with Rfree, Rcomplete relies on a method of reducing bias from the structural model. We compare two different methods reducing model bias and question the widely spread notion that random parameter shifts are required for this purpose. We show that Rcomplete has as little statistical bias as Rfree with the benefit of a much smaller variance. Because the calculation of Rcomplete is based on the entire dataset instead of a small subset, it allows the estimation of maximum likelihood parameters even for small datasets. Rcomplete enables maximum likelihood-based refinement to be extended to virtually all areas of crystallographic structure determination including high-pressure studies, neutron diffraction studies, and datasets from free electron lasers.},
author = {Luebben, Jens and Gruene, Tim},
doi = {10.1073/pnas.1502136112},
file = {:Users/cmax/Dropbox/Literature/luebben{\_}gruene2015.pdf:pdf},
isbn = {1502136112},
issn = {0027-8424},
journal = {Proc. Natl. Acad. Sci. U. S. A.},
pages = {201502136},
title = {{New method to compute R complete enables maximum likelihood refinement for small datasets}},
url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1502136112},
year = {2015}
}

@proceedings{LURE1986phase1and2,
  title = {{\mockalph{bbbbb}}Proceedings of the EEC Cooperative Workshop on Position-Sensitive Detector Software (Phases I \& II)},
  year = 1986,
  editor = {Bricogne, G.},
  publisher = {LURE},
  organization = {Centre National de la Recherche Scientifique Universit\'{e} Paris-Sud}
}

@proceedings{LURE1986phase3,
  title = {{\mockalph{ccccc}}Proceedings of the EEC Cooperative Workshop on Position-Sensitive Detector Software (Phase III)},
  year = 1986,
  editor = {Bricogne, G.},
  publisher = {LURE},
  organization = {Centre National de la Recherche Scientifique Universit\'{e} Paris-Sud}
}

@article{McCoy2007,
abstract = {Phaser is a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented in Phaser have been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations between F(+) and F(-), give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use mean F and anomalous differences DeltaF. One of the design concepts of Phaser was that it be capable of a high degree of automation. To this end, Phaser (written in C++) can be called directly from Python, although it can also be called using traditional CCP4 keyword-style input. Phaser is a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community.},
author = {McCoy, Airlie J. and Grosse-Kunstleve, Ralf W. and Adams, Paul D. and Winn, Martyn D. and Storoni, Laurent C. and Read, Randy J.},
doi = {10.1107/S0021889807021206},
file = {:Users/cmax/Dropbox/Literature/mccoy{\_}phaser{\_}2007.pdf:pdf},
isbn = {0021-8898},
issn = {00218898},
journal = {Journal of Applied Crystallography},
keywords = {Computer programs,Likelihood,Molecular replacement,SAD phasing,Structural genomics},
number = {4},
pages = {658--674},
pmid = {19461840},
publisher = {International Union of Crystallography},
title = {{Phaser crystallographic software}},
volume = {40},
year = {2007}
}


@article{Murshudov2011,
abstract = {This paper describes various components of the macromolecular crystallographic refinement program REFMAC5, which is distributed as part of the CCP4 suite. REFMAC5 utilizes different likelihood functions depending on the diffraction data employed (amplitudes or intensities), the presence of twinning and the availability of SAD/SIRAS experimental diffraction data. To ensure chemical and structural integrity of the refined model, REFMAC5 offers several classes of restraints and choices of model parameterization. Reliable models at resolutions at least as low as 4 {\AA} can be achieved thanks to low-resolution refinement tools such as secondary-structure restraints, restraints to known homologous structures, automatic global and local NCS restraints, `jelly-body' restraints and the use of novel long-range restraints on atomic displacement parameters (ADPs) based on the Kullback-Leibler divergence. REFMAC5 additionally offers TLS parameterization and, when high-resolution data are available, fast refinement of anisotropic ADPs. Refinement in the presence of twinning is performed in a fully automated fashion. REFMAC5 is a flexible and highly optimized refinement package that is ideally suited for refinement across the entire resolution spectrum encountered in macromolecular crystallography.},
author = {Murshudov, Garib N. and Skub{\'{a}}k, Pavol and Lebedev, Andrey A. and Pannu, Navraj S. and Steiner, Roberto A. and Nicholls, Robert A. and Winn, Martyn D. and Long, Fei and Vagin, Alexei A.},
doi = {10.1107/S0907444911001314},
file = {:Users/cmax/Dropbox/Literature/murshudov{\_}refmac{\_}2011.pdf:pdf},
isbn = {0907444911001},
issn = {09074449},
journal = {Acta Crystallographica Section D: Biological Crystallography},
keywords = {REFMAC5,refinement},
number = {4},
pages = {355--367},
pmid = {21460454},
title = {{REFMAC5 for the refinement of macromolecular crystal structures}},
volume = {67},
year = {2011}
}

@article{Nederlof2013,
  abstract = {When protein crystals are submicrometre-sized, X-ray radiation damage precludes conventional diffraction data collection. For crystals that are of the order of 100 nm in size, at best only single-shot diffraction patterns can be collected and rotation data collection has not been possible, irrespective of the diffraction technique used. Here, it is shown that at a very low electron dose (at most 0.1 e(-) {\AA}(-2)), a Medipix2 quantum area detector is sufficiently sensitive to allow the collection of a 30-frame rotation series of 200 keV electron-diffraction data from a single ∼100 nm thick protein crystal. A highly parallel 200 keV electron beam ($\lambda$ = 0.025 {\AA}) allowed observation of the curvature of the Ewald sphere at low resolution, indicating a combined mosaic spread/beam divergence of at most 0.4°. This result shows that volumes of crystal with low mosaicity can be pinpointed in electron diffraction. It is also shown that strategies and data-analysis software (MOSFLM and SCALA) from X-ray protein crystallography can be used in principle for analysing electron-diffraction data from three-dimensional nanocrystals of proteins.},
  author = {Nederlof, Igor and {Van Genderen}, Eric and Li, Yao Wang and Abrahams, Jan Pieter},
  doi = {10.1107/S0907444913009700},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Nederlof et al. - 2013 - A Medipix quantum area detector allows rotation electron diffraction data collection from submicrometre three-d.pdf:pdf},
  isbn = {10.1107/S0907444913009700},
  issn = {09074449},
  journal = {Acta Crystallographica Section D: Biological Crystallography},
  mendeley-groups = {electron diffraction},
  number = {7},
  pages = {1223--1230},
  pmid = {23793148},
  title = {{A Medipix quantum area detector allows rotation electron diffraction data collection from submicrometre three-dimensional protein crystals}},
  volume = {69},
  year = {2013}
}


@article{Parkhurst2014,
  author = "Parkhurst, James M. and Brewster, Aaron S. and Fuentes-Montero, Luis and Waterman, David G. and Hattne, Johan and Ashton, Alun W. and Echols, Nathaniel and Evans, Gwyndaf and Sauter, Nicholas K. and Winter, Graeme",
  title = "{{\it dxtbx}: the diffraction experiment toolbox}",
  journal = "Journal of Applied Crystallography",
  year = "2014",
  volume = "47",
  number = "4",
  pages = "1459--1465",
  month = "Aug",
  doi = {10.1107/S1600576714011996},
}

@article{Parkhurst2016,
  author={
    Parkhurst, James M and
    Winter, Graeme and
    Waterman, David G and
    Fuentes-Montero, Luis and
    Gildea, Richard J and
    Murshudov, Garib N and
    Evans, Gwyndaf},
  title={Robust background modelling in \dials},
  journal={Journal of Applied Crystallography},
  year={2016},
  volume={49},
  pages = {1912–-1921},
}

@article{Parkhurst2017,
  abstract = {An algorithm for modelling the background for each Bragg reflection in a series of X-ray diffraction images containing Debye{\{}--{\}}Scherrer diffraction from ice in the sample is presented. The method involves the use of a global background model which is generated from the complete X-ray diffraction data set. Fitting of this model to the background pixels is then performed for each reflection independently. The algorithm uses a static background model that does not vary over the course of the scan. The greatest improvement can be expected for data where ice rings are present throughout the data set and the local background shape at the size of a spot on the detector does not exhibit large time-dependent variation. However, the algorithm has been applied to data sets whose background showed large pixel variations (variance/mean {\textgreater} 2) and has been shown to improve the results of processing for these data sets. It is shown that the use of a simple flat-background model as in traditional integration programs causes systematic bias in the background determination at ice-ring resolutions, resulting in an overestimation of reflection intensities at the peaks of the ice rings and an underestimation of reflection intensities either side of the ice ring. The new global background-model algorithm presented here corrects for this bias, resulting in a noticeable improvement in {\{}$\backslash$it R{\}} factors following refinement.},
  author = {Parkhurst, James M and Thorn, Andrea and Vollmar, Melanie and Winter, Graeme and Waterman, David G and Fuentes-Montero, Luis and Gildea, Richard J and Murshudov, Garib N and Evans, Gwyndaf},
  doi = {10.1107/S2052252517010259},
  journal = {IUCrJ},
  keywords = { AUSPEX, DIALS, X-ray crystallography, X-ray diffraction, data analysis, data processing, data quality, ice rings, refinement,protein structure},
  month = {sep},
  number = {5},
  pages = {626--638},
  title = {{Background modelling of diffraction data in the presence of ice rings}},
  url = {https://doi.org/10.1107/S2052252517010259},
  volume = {4},
  year = {2017}
}

@article{Read2016,
abstract = {The crystallographic diffraction experiment measures Bragg intensities; crystallographic electron-density maps and other crystallographic calculations in phasing require structure-factor amplitudes. If data were measured with no errors, the structure-factor amplitudes would be trivially proportional to the square roots of the intensities. When the experimental errors are large, and especially when random errors yield negative net intensities, the conversion of intensities and their error estimates into amplitudes and associated error estimates becomes nontrivial. Although this problem has been addressed intermittently in the history of crystallographic phasing, current approaches to accounting for experimental errors in macromolecular crystallography have numerous significant defects. These have been addressed with the formulation of LLGI, a log-likelihood-gain function in terms of the Bragg intensities and their associated experimental error estimates. LLGI has the correct asymptotic behaviour for data with large experimental error, appropriately downweighting these reflections without introducing bias. LLGI abrogates the need for the conversion of intensity data to amplitudes, which is usually performed with the French and Wilson method [French {\&} Wilson (1978), Acta Cryst. A35, 517-525], wherever likelihood target functions are required. It has general applicability for a wide variety of algorithms in macromolecular crystallography, including scaling, characterizing anisotropy and translational noncrystallographic symmetry, detecting outliers, experimental phasing, molecular replacement and refinement. Because it is impossible to reliably recover the original intensity data from amplitudes, it is suggested that crystallographers should always deposit the intensity data in the Protein Data Bank.},
author = {Read, Randy J. and McCoy, Airlie J.},
doi = {10.1107/S2059798315013236},
file = {:Users/cmax/Dropbox/Literature/read{\_}mccoy{\_}2016.pdf:pdf},
issn = {20597983},
journal = {Acta Crystallographica Section D: Structural Biology},
keywords = {intensity-measurement errors,likelihood},
number = {3},
pages = {375--387},
pmid = {26960124},
title = {{A log-likelihood-gain intensity target for crystallographic phasing that accounts for experimental error}},
volume = {72},
year = {2016}
}

@article{Reeke1984,
  author = "Reeke, Jnr, G. N.",
  title = "{Eigenvalue filtering in the refinement of crystal and orientation parameters for oscillation photography}",
  journal = "Journal of Applied Crystallography",
  year = "1984",
  volume = "17",
  number = "4",
  pages = "238--243",
  month = "Aug",
  doi = {10.1107/S0021889884011444},
}

@article{Sauter2006,
  abstract = {Procedures for detecting the point-group symmetry of macromolecular data sets are examined and enhancements are proposed. To validate a point group, it is sufficient to compare pairs of Bragg reflections that are related by each of the group's component symmetry operators. Correlation is commonly expressed in the form of a single statistical quantity (such as Rmerge) that incorporates information from all of the observed reflections. However, the usual practice of weighting all pairs of symmetry-related intensities equally can obscure the fact that the various symmetry operators of the point group contribute differing fractions of the total set. In some cases where particular symmetry elements are significantly under-represented, statistics calculated globally over all observations do not permit conclusions about the point group and Patterson symmetry. The problem can be avoided by repartitioning the data in a way that explicitly takes note of individual operators. The new analysis methods, incorporated into the program LABELIT (http://cci.lbl.gov/labelit), can be performed early enough during data acquisition, and are quick enough that it is feasible to pause to optimize the data collection strategy.},
  author = {Sauter, Nicholas K. and Grosse-Kunstleve, Ralf W. and Adams, Paul D.},
  doi = {10.1107/S0021889805042299},
  file = {:home/david/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Sauter, Grosse-Kunstleve, Adams - 2006 - Improved statistics for determining the Patterson symmetry from unmerged diffraction intensitie.pdf:pdf},
  isbn = {0021889805},
  issn = {0021-8898},
  journal = {Journal of Applied Crystallography},
  month = {mar},
  number = {2},
  pages = {158--168},
  publisher = {International Union of Crystallography},
  title = {{Improved statistics for determining the Patterson symmetry from unmerged diffraction intensities}},
  url = {http://scripts.iucr.org/cgi-bin/paper?S0021889805042299},
  volume = {39},
  year = {2006}
}

@data{sbdb288,
 author = { Hattne, J and  de la Cruz, J and  Gonen, T   },
 publisher = { SBGrid Data Bank },
 title = { Micro-Electron Diffraction data for: Trypsin. PDB Code 5k7r },
 year = { 2017 },
 doi = { 10.15785/SBGRID/288 },
 url = { http://dx.doi.org/10.15785/SBGRID/288 }
}

@article{Stanton1992,
  author = "Stanton, M. and Phillips, W. C. and Li, Y. and Kalata, K.",
  title = "{Correcting spatial distortions and nonuniform response in area detectors}",
  journal = "Journal of Applied Crystallography",
  year = "1992",
  volume = "25",
  number = "5",
  pages = "549--558",
  month = "Oct",
  doi = {10.1107/S0021889892004035},
  url = {https://doi.org/10.1107/S0021889892004035},
  abstract = {Software and hardware methods have been developed to correct images for spatial and intensity distortions produced by optical and electro-optical components in X-ray area detectors. Spatial distortions are divided into two types: gross distortions produced by the inherent properties of the detector components and local distortions formed by irregularities in the components. Intensity distortions are separated into three types: those caused by background nonuniformity; those resulting from pixel-dependent nonuniform intensity response; and those resulting from time-dependent variations in background and incident beam intensity. From background, flat-field, reference and mask images, `forward' and `reverse' interpolation tables are generated to correct for spatial distortions and a lookup table is generated to correct for nonuniform sensitivity. The routines have been used successfully on four different area detectors to correct entire images or to correct intensities of individual Bragg peaks. The spatial-distortion correction is good to within 0.1 pixels and the nonuniformity correction to [less-than 2%.},
}

@article{Stanton1993,
  title = "Area detector design Part I. Formulation of design criteria and application to X-ray crystallography",
  journal = "Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment",
  volume = "325",
  number = "3",
  pages = "550 - 557",
  year = "1993",
  issn = "0168-9002",
  doi = "https://doi.org/10.1016/0168-9002(93)90404-6",
  url = "http://www.sciencedirect.com/science/article/pii/0168900293904046",
  author = "Martin Stanton"
}

@article{Steller1997,
  author = "Steller, I. and Bolotovsky, R. and Rossmann, M. G.",
  title = "{An Algorithm for Automatic Indexing of Oscillation Images using Fourier Analysis}",
  journal = "Journal of Applied Crystallography",
  year = "1997",
  volume = "30",
  number = "6",
  pages = "1036--1040",
  month = "Dec",
  doi = {10.1107/S0021889897008777},
  url = {https://doi.org/10.1107/S0021889897008777},
  abstract = {A fast and reliable algorithm has been developed for auto-indexing oscillation images. The observed reflection positions are used to compute the corresponding reciprocal-lattice vectors assuming a stationary crystal. These vectors are then projected onto a chosen direction. The projections are subjected to a one-dimensional Fourier analysis. A large Fourier term will be found that has a periodicity corresponding to the interplanar distance if the chosen direction happens to be perpendicular to a set of widely separated reciprocal-lattice planes. Exploration of such directions over a hemisphere establishes the best potential basis vectors of the real cell. The program has successfully determined the lengths and directions of basis vectors for numerous unit cells having cell dimensions ranging from 16 to 668{\AA} and oscillation ranges from 0.2 to 2.0{$^\circ$}.},
}

@article{VanGenderen2016,
  abstract = {Until recently, structure determination by transmission electron microscopy of beam-sensitive three-dimensional nanocrystals required electron diffraction tomography data collection at liquid-nitrogen temperature, in order to reduce radiation damage. Here it is shown that the novel Timepix detector combines a high dynamic range with a very high signal-to-noise ratio and single-electron sensitivity, enabling ab initio phasing of beam-sensitive organic compounds. Low-dose electron diffraction data (∼0.013 e(-) {\AA}(-2) s(-1)) were collected at room temperature with the rotation method. It was ascertained that the data were of sufficient quality for structure solution using direct methods using software developed for X-ray crystallography (XDS, SHELX) and for electron crystallography (ADT3D/PETS, SIR2014).},
  author = {{Van Genderen}, E. and Clabbers, M. T B and Das, P. P. and Stewart, A. and Nederlof, I. and Barentsen, K. C. and Portillo, Q. and Pannu, N. S. and Nicolopoulos, S. and Gruene, T. and Abrahams, J. P.},
  doi = {10.1107/S2053273315022500},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Van Genderen et al. - 2016 - Ab initio structure determination of nanocrystals of organic pharmaceutical compounds by electron diffracti.pdf:pdf},
  issn = {20532733},
  journal = {Acta Crystallographica Section A: Foundations and Advances},
  keywords = {Timepix quantum area detector,carbamazepine,electron diffraction structure determination,electron nanocrystallography,nicotinic acid},
  mendeley-groups = {electron diffraction},
  pages = {236--242},
  pmid = {26919375},
  publisher = {International Union of Crystallography},
  title = {{Ab initio structure determination of nanocrystals of organic pharmaceutical compounds by electron diffraction at room temperature using a Timepix quantum area direct electron detector}},
  volume = {72},
  year = {2016}
}


@article{Waterman2010,
   author = {Waterman, David and Evans, Gwyndaf},
   title = {Estimation of errors in diffraction data measured by CCD area detectors},
   journal = {Journal of Applied Crystallography},
   volume = {43},
   number = {6},
   pages = {1356-1371},
   abstract = {Current methods for diffraction-spot integration from CCD area detectors typically underestimate the errors in the measured intensities. In an attempt to understand fully and identify correctly the sources of all contributions to these errors, a simulation of a CCD-based area-detector module has been produced to address the problem of correct handling of data from such detectors. Using this simulation, it has been shown how, and by how much, measurement errors are underestimated. A model of the detector statistics is presented and an adapted summation integration routine that takes this into account is shown to result in more realistic error estimates. In addition, the effect of correlations between pixels on two-dimensional profile fitting is demonstrated and the problems surrounding improvements to profile-fitting algorithms are discussed. In practice, this requires knowledge of the expected correlation between pixels in the image.},
   keywords = {error estimation
CCD area detectors
detector simulation
pixel correlation},
   year = {2010}
}

@article{Waterman2016,
  author = "Waterman, David G. and Winter, Graeme and Gildea, Richard J. and Parkhurst, James M. and Brewster, Aaron S. and Sauter, Nicholas K. and Evans, Gwyndaf",
  title = "{Diffraction-geometry refinement in the {\it DIALS} framework}",
  journal = "Acta Crystallographica Section D",
  year = "2016",
  volume = "72",
  number = "4",
  pages = "558--575",
  month = "Apr",
  doi = {10.1107/S2059798316002187},
  _url = {http://dx.doi.org/10.1107/S2059798316002187},
  abstract = {Rapid data collection and modern computing resources provide the opportunity to revisit the task of optimizing the model of diffraction geometry prior to integration. A comprehensive description is given of new software that builds upon established methods by performing a single global refinement procedure, utilizing a smoothly varying model of the crystal lattice where appropriate. This global refinement technique extends to multiple data sets, providing useful constraints to handle the problem of correlated parameters, particularly for small wedges of data. Examples of advanced uses of the software are given and the design is explained in detail, with particular emphasis on the flexibility and extensibility it entails.},
  keywords = {global refinement, DIALS framework, centroid refinement},
}

@article{Winter2018,
  abstract = {{\textless}p{\textgreater} The {\textless}italic{\textgreater}DIALS{\textless}/italic{\textgreater} project is a collaboration between Diamond Light Source, Lawrence Berkeley National Laboratory and CCP4 to develop a new software suite for the analysis of crystallographic X-ray diffraction data, initially encompassing spot finding, indexing, refinement and integration. The design, core algorithms and structure of the software are introduced, alongside results from the analysis of data from biological and chemical crystallography experiments. {\textless}/p{\textgreater}},
  author = {Winter, Graeme and Waterman, David G. and Parkhurst, James M. and Brewster, Aaron S. and Gildea, Richard J. and Gerstel, Markus and Fuentes-Montero, Luis and Vollmar, Melanie and Michels-Clark, Tara and Young, Iris D. and Sauter, Nicholas K. and Evans, Gwyndaf},
  doi = {10.1107/S2059798317017235},
  file = {:home/david/Dropbox/my{\_}papers/Winter2018{\_}DIALS.pdf:pdf},
  issn = {2059-7983},
  journal = {Acta Crystallographica Section D Structural Biology},
  keywords = {d,data processing,dials,iucr,methods development,org,supporting information,supporting information at journals,this article has,x-ray diffraction},
  number = {2},
  pages = {85--97},
  publisher = {International Union of Crystallography},
  title = {{{\textless}i{\textgreater}DIALS{\textless}/i{\textgreater} : implementation and evaluation of a new integration package}},
  url = {http://scripts.iucr.org/cgi-bin/paper?S2059798317017235},
  volume = {74},
  year = {2018}
}

@article{Yonekura2002,
abstract = {The scattering cross-section of atoms in biological macromolecules for both elastically and inelastically scattered electrons is approximately 100,000 times larger than that for x-ray. Therefore, much smaller ({\textless}1 microm) and thinner ({\textless}0.01 microm) protein crystals than those used for x-ray crystallography can be used to analyze the molecular structures by electron crystallography. But, inelastic scattering is a serious problem. We examined electron diffraction data from thin three-dimensional (3-D) crystals (600-750 A thick) and two-dimensional (2-D) crystals (approximately 60 A thick), both at 93 K, with an energy filtering electron microscope operated at an accelerating voltage of 200 kV. Removal of inelastically scattered electrons significantly improved intensity data statistics and R(Friedel) factor in every resolution range up to 3-A resolution. The effect of energy filtering was more prominent for thicker crystals but was significant even for thin crystals. These filtered data sets showed better intensity statistics even in comparison with data sets collected at 4 K and an accelerating voltage of 300 kV without energy filtering. Thus, the energy filter will be an effective and important tool in the structure analysis of thin 3-D and 2-D crystals, particularly when data are collected at high tilt angle.},
author = {Yonekura, Koji and Maki-Yonekura, Saori and Namba, Keiichi},
doi = {10.1016/S0006-3495(02)75619-1},
file = {:Users/cmax/Dropbox/Literature/yonekura{\_}2002.pdf:pdf},
issn = {0006-3495},
journal = {Biophysical journal},
number = {5},
pages = {2784--2797},
pmid = {11964264},
publisher = {Elsevier},
title = {{Quantitative comparison of zero-loss and conventional electron diffraction from two-dimensional and thin three-dimensional protein crystals.}},
url = {http://dx.doi.org/10.1016/S0006-3495(02)75619-1},
volume = {82},
year = {2002}
}


@article{Yonekura2015,
  abstract = {Membrane proteins and macromolecular complexes often yield crystals too small or too thin for even the modern synchrotron X-ray beam. Electron crystallography could provide a powerful means for structure determination with such undersized crystals, as protein atoms diffract electrons four to five orders of magnitude more strongly than they do X-rays. Furthermore, as electron crystallography yields Coulomb potential maps rather than electron density maps, it could provide a unique method to visualize the charged states of amino acid residues and metals. Here we describe an attempt to develop a methodology for electron crystallography of ultrathin (only a few layers thick) 3D protein crystals and present the Coulomb potential maps at 3.4-{\AA} and 3.2-{\AA} resolution, respectively, obtained from Ca(2+)-ATPase and catalase crystals. These maps demonstrate that it is indeed possible to build atomic models from such crystals and even to determine the charged states of amino acid residues in the Ca(2+)-binding sites of Ca(2+)-ATPase and that of the iron atom in the heme in catalase.},
  author = {Yonekura, Koji and Kato, Kazuyuki and Ogasawara, Mitsuo and Tomita, Masahiro and Toyoshima, Chikashi},
  doi = {10.1073/pnas.1500724112},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Yonekura et al. - 2015 - Electron crystallography of ultrathin 3D protein crystals Atomic model with charges.pdf:pdf},
  issn = {1091-6490},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  mendeley-groups = {electron diffraction},
  number = {11},
  pages = {3368--3373},
  pmid = {25730881},
  title = {{Electron crystallography of ultrathin 3D protein crystals: Atomic model with charges.}},
  url = {http://www.pnas.org/content/112/11/3368.short},
  volume = {112},
  year = {2015}
}

@Article{rotmethod_e:2010,
  author = "Zhang, D. and Oleynikov, P. and Hovm{\"o}ller, S. and Zou, X.",
  title = "Collecting 3D electron diffraction data by the rotation method",
  journal = "Z. Kristallogr.",
  year = "2010",
  volume = "225",
  pages = "94--102",
}

@article {review_adt_red:2015,
  author = "Yun, Y. and Zou, X. and Hovm{\"o}ller, S. and Wan, W.",
  title = "Three--dimensional electron diffraction as a complementary
  	technique to powder X--ray diffraction for phase identification and structure solution of powders",
  journal = "IUCrJ",
  year = "2015",
  volume = "2",
  pages = "267--282",
}


@article{adt:2007,
Author = {Kolb, U. and Gorelik, T. and K{\"u}bel, C. and Otten, M. T. and Hubert, D.},
Title = {{Towards automated diffraction tomography: Part I - Data acquisition}},
Journal = {{Ultramicroscopy}},
Year = "2007",
Volume = "107",
Pages = "507--513",
}

@Article{unwin-henderson:1975,
author="Unwin, P. N. T. and Henderson, R.",
title="Olecular Structure Determination by Electron Microscopy of Unstained Crystalline Specimens",
journal="J. Mol. Biol.",
year="1975",
volume="94",
pages="425--440",
}

@Book{glaeser_downing_derosier:2007,
  author = "Glaeser, R. M. and Downing, K. and DeRosier, D.",
  title = "Electron Crystallography of Biological Macromolecules",
  publisher = "Oxford Univ. Press",
  year = "2007",
}

@Book{dorset:1995,
  author = "Dorset, D. L.",
  title = "Structural Electron Crystallography",
  publisher = "Springer",
  year = "1995",
  series = "Language of Science",
}

@Book{zou:2011,
  author = "Zou, X. and Hovm{\"o}ller, S. and Oleynikov, P.",
  title = "Electron Crystallography",
  publisher = "Oxford Univ. Press",
  year = "2011",
}
@Book{vainshtein:1964,
  author = "Vainshtein, B. K.",
  title = "Structure Analysis by Electron Diffraction",
  publisher = "Pergamon Press",
  year = "1964",
}

@Article{         zeo_adt:2014,
  author        = "Mugnaioli, E. and Kolb, U.",
  title         = "Structure solution of zeolites by automated electron
                  diffraction tomography --- Impact and treatment of
                  preferential orientation",
  journal       = "Microporous Mesoporous Mater.",
  volume        = "189",
  pages         = "107--114",
  year          = "2014"
}

@article{weirich:1996,
 author = "Weirich, T. E. and Ramlau, R. and Simon, A. and Hovm{\"o}ller, S. and Zou, X.",
 title  = "A crystal structure determined with 0.02~\AA{} accuracy by electron
 microscopy",
 journal = "Nature",
 year = "1996",
 pages = "144--146",
}

@article{dorset:1992,
  author = "Dorset, D. L.",
  title  = "Direct Methods in Electron Crystallography --- Structure Analysis of
  Boric Acid",
  journal = "Acta Crystallogr.",
  year = "1992",
  volume = "A48",
  pages = "568--574",
}

@article {palatinus:2017,
        author = {Palatinus, L. and Br{\'a}zda, P. and Boullay, P. and Perez, O.
        and Klementov{\'a}, M. and Petit, S. and Eigner, V. and Zaarour, M. and Mintova, S.},
        title = {Hydrogen positions in single nanocrystals revealed by electron diffraction},
        volume = {355},
        pages = {166--169},
        year = {2017},
        journal = {Science}
}

@article{pflugrath:1999,
author = "Pflugrath, J. W.",
title = "{The finer things in X-ray diffraction data collection}",
journal = "Acta Crystallogr",
year = "1999",
volume = "D55",
pages = "1718--1725",
}

@Article{lenscorr_2dx:2006,
author="Capitani, G. C. and Oleynikov, P. and Hovm{\"o}ller, S. and Mellini, M.",
title="A practical method to detect and correct for lens distortion in the TEM",
journal="Ultramicroscopy",
year="2006",
volume="106",
pages="66--74",
}

@article{dials_adsc:2016a,
author = "Keegan, Ronan and Waterman, David G. and Hopper, David J. and Coates, Leighton and Taylor, Graham and Guo, Jingxu and Coker, Alun R. and Erskine, Peter T. and Wood, Steve P. and Cooper, Jonathan B.",
title = "{The 1.1{\AA} resolution structure of a periplasmic phosphate-binding protein from {\it Stenotrophomonas maltophilia}: a crystallization contaminant identified by molecular replacement using the entire Protein Data Bank}",
journal = "Acta Crystallogr",
year = "2016",
volume = "D72",
pages = "933--943",
}

@article{dials_adsc:2016b,
author = "Khasnis, M. D. and  Halkidis, K. and Bhardwaj, A. and Root, M. J.",
title = "Receptor Activation of HIV-1 Env Leads to Asymmetric Exposure of the gp41 Trimer",
journal = "PLoS Pathog",
year = "2016",
volume = "12",
pages = "e1006098",
}

@article{gemmi_adt:2015,
author = "Gemmi, Mauro and La Placa, Maria G. I. and Galanis, Athanassios S. and Rauch, Edgar F. and Nicolopoulos, Stavros",
title = "{Fast electron diffraction tomography}",
journal = "J Appl. Crystallogr",
year = "2015",
volume = "48",
pages = "718--727",
}

@article{prigo:2015,
author = "Waltersperger, Sandro and Olieric, Vincent and Pradervand, Claude and
Glettig, Wayne and Salathe, Marco and Fuchs, Martin R. and Curtin, Adrian and
Wang, Xiaoqiang and Ebner, Simon and Panepucci, Ezequiel and Weinert, Tobias and
Schulze-Briese, Clemens and Wang, Meitian",
title = "{PRIGo: a new multi-axis goniometer for macromolecular
crystallography}",
journal = "J. Synchrotron Radiat.",
year = "2015",
volume = "22",
pages = "895--900",
}

@article{nm_gonio:2013,
  author={B Knapp and E Marsh and F Cipriani and D Arneson and D Oss and M Liebers and E Keller},
  title={Nanometer-level axis of rotation metrology for a high-precision macromolecular X-ray diffractometer},
  journal={J Phys: Conf. Ser.},
  volume={425},
  pages={012012},
  year={2013},
}

@article{Shi2016,
abstract = {The formation of large, well-ordered crystals for crystallographic experiments remains a crucial bottleneck to the structural understanding of many important biological systems. To help alleviate this problem in crystallography, we have developed the MicroED method for the collection of electron diffraction data from 3D microcrystals and nanocrystals of radiation-sensitive biological material. In this approach, liquid solutions containing protein microcrystals are deposited on carbon-coated electron microscopy grids and are vitrified by plunging them into liquid ethane. MicroED data are collected for each selected crystal using cryo-electron microscopy, in which the crystal is diffracted using very few electrons as the stage is continuously rotated. This protocol gives advice on how to identify microcrystals by light microscopy or by negative-stain electron microscopy in samples obtained from standard protein crystallization experiments. The protocol also includes information about custom-designed equipment for controlling crystal rotation and software for recording experimental parameters in diffraction image metadata. Identifying microcrystals, preparing samples and setting up the microscope for diffraction data collection take approximately half an hour for each step. Screening microcrystals for quality diffraction takes roughly an hour, and the collection of a single data set is ∼10 min in duration. Complete data sets and resulting high-resolution structures can be obtained from a single crystal or by merging data from multiple crystals.},
author = {Shi, Dan and Nannenga, Brent L. and de la Cruz, M. Jason and Liu, Jinyang and Sawtelle, Steven and Calero, Guillermo and Reyes, Francis E and Hattne, Johan and Gonen, Tamir},
doi = {10.1038/nprot.2016.046},
file = {:Users/cmax/Dropbox/Literature/shi{\_}gonen{\_}nprot{\_}2016.pdf:pdf},
issn = {1750-2799},
journal = {Nature protocols},
number = {5},
pages = {895--904},
pmid = {27077331},
publisher = {Nature Publishing Group},
title = {{The collection of MicroED data for macromolecular crystallography.}},
url = {http://dx.doi.org/10.1038/nprot.2016.046},
volume = {11},
year = {2016}
}

@article{Wan2013,
  abstract = {Implementation of a computer program package for automated collection and processing of rotation electron diffraction (RED) data is described. The software package contains two computer programs: RED data collection and RED data processing. The RED data collection program controls the transmission electron microscope and the camera. Electron beam tilts at a fine step (0.05-0.20°) are combined with goniometer tilts at a coarse step (2.0-3.0°) around a common tilt axis, which allows a fine relative tilt to be achieved between the electron beam and the crystal in a large tilt range. An electron diffraction (ED) frame is collected at each combination of beam tilt and goniometer tilt. The RED data processing program processes three-dimensional ED data generated by the RED data collection program or by other approaches. It includes shift correction of the ED frames, peak hunting for diffraction spots in individual ED frames and identification of these diffraction spots as reflections in three dimensions. Unit-cell parameters are determined from the positions of reflections in three-dimensional reciprocal space. All reflections are indexed, and finally a list with hkl indices and intensities is output. The data processing program also includes a visualizer to view and analyse three-dimensional reciprocal lattices reconstructed from the ED frames. Details of the implementation are described. Data collection and data processing with the software RED are demonstrated using a calcined zeolite sample, silicalite-1. The structure of the calcined silicalite-1, with 72 unique atoms, could be solved from the RED data by routine direct methods.},
  author = {Wan, Wei and Sun, Junliang and Su, Jie and Hovm{\"{o}}ller, Sven and Zou, Xiaodong},
  doi = {10.1107/S0021889813027714},
  file = {:home/fcx32934/Documents/Mendeley Desktop/Wan2013{\_}RED.pdf:pdf},
  isbn = {0021889813},
  issn = {00218898},
  journal = {Journal of Applied Crystallography},
  keywords = {Computer programs,Electron diffraction,Electron diffraction tomography,Rotation electron diffraction,Structure analysis,Three-dimensional electron diffraction},
  mendeley-groups = {electron diffraction},
  number = {6},
  pages = {1863--1873},
  pmid = {24282334},
  title = {{Three-dimensional rotation electron diffraction: Software RED for automated data collection and data processing}},
  volume = {46},
  year = {2013}
}

@article{Weirich2000,
abstract = { The structure of a new modification of Ti2Se, the beta-phase, and several related inorganic crystal structures containing elements with atomic numbers between 16 and 40 have been solved by quasi-automatic direct methods from single-crystal electron diffraction patterns of nanometre-size crystals, using the kinematical aproxi-mation. The crystals were several thousand times smaller than the minimum size required for single-crystal X-ray diffraction. Atomic coordinates were found with an average accuracy of 0.2 A or better. Experimental data were obtained by standardized techniques for recording and quantifying electron diffraction patterns. The SIR97 program for solving crystal structures from three-dimensional X-ray diffraction data by direct methods was modified to work also with two-dimensional electron diffraction data. },
author = {Weirich, Thomas E. and Zou, Xiaodong and Ramlau, Reiner and Simon, Arndt and Cascarano, Giovanni Luca and Giacovazzo, Carmelo and Hovm{\"{o}}ller, Sven},
doi = {10.1107/S0108767399009605},
file = {:Users/cmax/Dropbox/Literature/weirich{\_}hovmoller2000.pdf:pdf},
isbn = {0108-7673},
issn = {01087673},
journal = {Acta Crystallographica Section A: Foundations of Crystallography},
number = {1},
pages = {29--35},
pmid = {10874414},
title = {{Structures of nanometre-size crystals determined from selected-area electron diffraction data}},
volume = {56},
year = {2000}
}