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| =Download=
| | CryoNAV is in active development and is not yet available for download. This page will be updated when the first public release is announced. |
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| CryoNAV is currently under development and not yet available for public download. However, the software is designed to integrate with various established cryo-EM tools. Below are the download links for the cryo-EM software packages that CryoNAV is planned to work with: | | For the current status, see the [[CryoNAV About#Status and roadmap|Status and roadmap]] section. |
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| ==Core Cryo-EM Processing Tools==
| | [[Category:Getting Started]] |
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| ===IMOD===
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| Image processing and 3D reconstruction package for electron tomography.
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| * '''Download:''' https://bio3d.colorado.edu/imod/download.html
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| * '''Description:''' Comprehensive software for processing cryo-electron tomographic data and generating 3D reconstructions
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| ===Dynamo===
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| Subtomogram averaging and cryo-ET processing software.
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| * '''Download:''' https://www.dynamo-em.org/
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| * '''Description:''' Flexible development tool for cryo-ET data processing with high-performance computing support
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| ===CTFfind===
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| Contrast transfer function estimation for electron micrographs.
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| * '''Download:''' https://grigoriefflab.umassmed.edu/ctf_estimation_ctffind_ctftilt
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| * '''Description:''' Program for finding CTFs of electron micrographs, developed by the Grigorieff Lab
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| ===RELION===
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| REgularised LIkelihood OptimisatioN for cryo-EM structure determination.
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| * '''Download:''' https://relion.readthedocs.io/
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| * '''GitHub:''' https://github.com/3dem/relion
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| * '''Description:''' Empirical Bayesian approach for single-particle analysis and refinement of cryo-EM data
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| ===EMAN2===
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| Scientific image processing suite with focus on cryo-EM and cryo-ET.
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| * '''GitHub:''' https://github.com/cryoem/eman2
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| * '''Description:''' Comprehensive greyscale image processing suite for transmission electron microscopy data
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| ==AI and Deep Learning Tools==
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| ===cryoCARE===
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| Content-aware image restoration for cryo-electron tomography.
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| * '''Download:''' https://pypi.org/project/cryoCARE/
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| * '''Description:''' Self-supervised deep learning approach for denoising cryo-electron tomographic data
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| ===DeepDeWedge===
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| Deep learning for denoising and missing wedge reconstruction.
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| * '''Download:''' https://github.com/MLI-lab/DeepDeWedge
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| * '''Description:''' Self-supervised deep learning method for simultaneous denoising and missing wedge reconstruction in cryo-ET
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| ==Installation Notes==
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| '''Prerequisites:''' Most cryo-EM software packages require:
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| * Linux or macOS operating systems
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| * CUDA-compatible GPUs for accelerated processing (recommended)
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| * MPI libraries for parallel processing
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| * Python environments (Anaconda/Miniconda recommended)
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| CryoNAV also provides integration with SLURM for cluster computing and Amazon S3 for cloud-based data storage and retrieval.
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| '''Important:''' Always check the specific system requirements and installation instructions for each software package before downloading. Many tools have dependencies on specific versions of libraries, compilers, or GPU drivers.
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| '''Academic Use:''' Most of these tools are freely available for academic research. Commercial users should check licensing requirements for each package.
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| ==Support and Documentation==
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| For CryoNAV-specific questions about planned integrations with these tools, please contact Paula Navarro (paula.navarro{at}unil.ch).
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| For issues with individual software packages, please refer to their respective documentation, forums, or support channels linked on their download pages.
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| ==See Also==
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| * [[Installation Guide]]
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| * [[Integration with Cryo-EM Tools]]
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| * [[Getting Started Home|Getting Started]]
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CryoNAV is in active development and is not yet available for download. This page will be updated when the first public release is announced.
For the current status, see the Status and roadmap section.
