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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.


Aims to subtomogram averaging of cryo Electron Tomography (cryo-ET) data with three main goals: first, Dynamo allows user-transparent adaptation to a variety of high-performance computing platforms such as GPUs or CPU clusters. Second, Dynamo implements user-friendliness through GUI interfaces and scripting resources. Third, Dynamo offers user-flexibility through a plugin API. Besides the alignment and averaging procedures, Dynamo includes native tools for visualization and analysis of results and data, as well as support for third party visualization software, such as Chimera UCSF or EMAN2.

RAZA / RApid 3D Z-crossings Algorithm

Segments low signal-to-noise ratio (SNR) data typical of 3D reconstructed volumes. RAZA is a detection algorithm that integrates a Laplacian of Gaussian (LoG) kernel, with arbitrary z-crossings and structural finger printing algorithms. It can detect edges in the tomographic volume, the edges are defined as regions exhibiting a “significant change” in voxel intensity compared to their surroundings. It defines each continuous contour within a tomographic volume as a discrete geometric object, as opposed to conducting simple pixel based edge delineation.

PEET / Particle Estimation for Electron Tomography

Serves for microtubule-kinesin motor domain complexes. PEET is a program that can align particles in 3-D subvolumes extracted from tomograms. This tool seeks the optimal alignment of each particle against a reference volume through several iterations. The program utilizes the parallel processing framework within IMOD software, and the lengthy computations can be distributed to multiple cores on one computer, to a set of linked workstations, or to a cluster.

TCCC / Thresholded Constrained Cross-Correlation

Improves results for Signal-to-Noise Ratios (SNR) lower than 0.1. TCCC allows to analyze macromolecules in thicker samples like whole cell or lower the defocus in thinner samples to push the first zero of the Contrast Transfer Function (CTF). TCCC uses statistics of the noise to automatically select only a small percentage of the Fourier coefficients to compute the cross-correlation. The thresholding has two main advantages in the cross-correlation score: first, reduces the influence of the noise; second, avoids the missing wedge normalization problem since we consider the same amount of coefficients for all possible pairs of subtomograms.