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Interfaces cryo-transmission electron microscopy (cryo-EM) data collection with computer image processing. Focus creates a user-friendly environment to import and manage data recorded by direct electron detectors and perform elemental image processing tasks in a high-throughput manner, while new data is being acquired at the microscope. It provides the functionality required to remotely monitor the progress of data collection and data processing, which is essential now that automation in cryo-EM allows a steady flow of images of single particles, two-dimensional crystals, or electron tomography data to be recorded in overnight sessions. The rapid detection of any errors that may occur greatly increases the productivity of recording sessions at the electron microscope.

ROME / Refinement and Optimization based on Machine lEarning for cryo-EM

Offers a clustering method for single-particle cryo-EM data. ROME enables efficient computation of thousands of reference-free class averages in a highly affordable fashion. It can markedly improve the quality and resolution of ab initio 3D models with angular reconstitution. This tool was evaluated using several cryoEM datasets. It shows the advantage of generative topographic mapping (GTM)-based unsupervised clustering in discerning subtle structural differences directly from 2D class averages corresponding to distinct conformations.


Enables rapid, unbiased, and high-throughput structure discovery of proteins and molecular complexes from single-particle cryo-EM data. The algorithms underlying cryoSPARC enable high-resolution reconstructions of research and drug targets within minutes of collecting microscope data, and without the need for prior knowledge of the target structure. Using cryoSPARC can remove the risk of biased results, allow the discovery of unexpected structures, and speed up Cryo-electron microscopy workflow by orders of magnitude. Furthermore, the graphical user interface allows multiple users within a laboratory to have separate accounts, access the program remotely, upload and share data sets, manage experimental results, launch computational tasks, and view results streaming in real time as they are computed.

SPRING / Single Particle Reconstruction from Images of kNown Geometry

Provides a single-particle based helical reconstruction package for electron cryo-micrographs. SPRING has been used to determine 3D structures of a variety of highly ordered and less ordered specimens. Spring provides the entire single-particle based work-flow required for helical reconstruction including: classification, helical symmetry determination and refinement tools, high-resolution structure refinement, and multi-symmetry structure refinement.

RELION / REgularised LIkelihood OptimisatioN

Employs an empirical Bayesian approach to refinement of (multiple) 3D reconstructions or 2D class averages in electron cryo-microscopy (cryo-EM). RELION is implemented as a stand-alone program, and its open-source C++ code is available for download. Application of RELION to both simulated and experimental data illustrates that reconstructions that are free from overfitting may be obtained in a highly objective manner, without compromising reconstruction quality and at acceptable computational costs.

cisTEM / Computational Imaging System for Transmission Electron Microscopy

Permits the treatment of cryo-electron microscopy (cryo-EM) images of macromolecular complexes. cisTEM is able to extract high-resolution 3D reconstructions form these images. It can deal with movies, micrographs and stacks of single-particle images, implementing a complete pipeline of processing steps. This tool is based on a maximum-likelihood algorithm. Users can define a combination of particle image stack, alignment parameters and a 3D reference structure.


Accelerates maximum-likelihood reconstructions. The speedup is by orders of magnitude, and the SubspaceEM algorithm produces similar quality reconstructions compared to the traditional maximum-likelihood formulation. This approach uses subspace approximations of the cryo-electron microscopy images and the structure projections, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300.


Allows for individual <1 MDa particle images to be aligned without frame averaging or linear trajectories. The lm-bfgs algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-electron microscopy.


Uses an approach based on prediction of specimen position during the tilt series from the position at previous tilts. SerialEM is a program that can acquire a variety of data from electron microscopes: tilt series for electron tomography, large image areas for 3-D reconstruction from serial sections, and images for reconstruction of macromolecules by single-particle methods. In addition to automating data acquisition, the program provides an integrated user interface for image acquisition, display, and storage.


Provides an image processing environment with a particular emphasis on transmission electron microscopy (TEM) structure determination. SPARX includes a graphical user interface that provides a complete graphical programming environment with a data/process-Xow infrastructure, an extensive library of Python scripts that perform speciWc TEM-related computational tasks, and a core library of fundamental C++ image processing functions. In addition, SPARX relies on the EMAN2 library and cctbx, the open-source computational crystallography library from PHENIX. The design of the system is such that future inclusion of other image processing libraries is a straightforward task. SPARX and all dependencies are free for academic use and available with complete source.