TomoBEAR is an open-source configurable and customizable modular pipeline for streamlined and parallelized processing of large-scale cryo-electron tomography data for subtomogram averaging.
TomoBEAR can assist you in large-scale processing of the tomographic data acquired on the electron microscope starting from the raw tilt series, possibly dose fractionated, containing fiducials or fiducial-less or already assembled tilt stacks up to sample volume 3D reconstruction and even further - to the sub-nanometer EM map of the biological structure of interest.
TomoBEAR is designed to operate in an automated manner minimizing user intervention where that is possible. The pipeline consists of over 20 different modules which integrate the original code of widely used cryo-ET/StA processing tools (e.g. IMOD, Dynamo, MotionCor2, AreTomo, GCTF/CTFFIN4), including the modern neural network tools (e.g. IsoNet, crYOLO), as well as our developments, including our StA framework called SUSAN, in a single workflow.
Since the number of the TomoBEAR parameters is huge, to help users cope with that we have carefully designed a predefined set of defaults which were chosen based on several different cryo-ET datasets, including standard cryo-ET benchmarks. A description of all modules and corresponding default values is given on the Modules page.
The execution can be sequential as well as CPU/GPU-parallelized and suitable for both standalone workstations and high-performance computing (HPC) clusters.
Implementation details and benchmarks may be found in our preprint:
Balyschew N, Yushkevich A, Mikirtumov V, Sanchez RM, Sprink T, Kudryashev M. Streamlined Structure Determination by Cryo-Electron Tomography and Subtomogram Averaging using TomoBEAR. [Preprint] 2023. bioRxiv doi: 10.1101/2023.01.10.523437
We have prepared a range of short (8-12 min) video tutorials explaining setup, usage and example output of the
TomoBEAR to help you get started with
TomoBEAR based on the ribosome tutorial:
TomoBEARversion and configure
TomoBEARand its dependencies;
TomoBEARloop for checking tilt series alignment results and fiducials refinement (if needed);
Detailed information on the installation, setup and usage as well as tutorials and example results can be found in the corresponding wiki.
TomoBEAR releases are available at the Releases page.
If you want to clone a specific
TomoBEAR version, please refer to the Setup > Get source code and binary > Clone specific version section on the wiki page Installation and Setup.
This work is licensed under multiple licenses:
If you use
TomoBEAR or its parts in your research, please cite
TomoBEAR along with all external software packages which you have used under
In case of any questions, issues or suggestions you may interact with us in one of the following ways:
If you wish to contribute, please, fork this repository and make a pull request back with your changes and a short description. For further details on contribution, please read our contribution guidelines on the GitHub repository.