TomoNet

TomoNet streamlines cryogenic electron tomography (cryoET) with automatic particle picking on flexible lattices to facilitate high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays.

Key Features:

• Automatic Particle Picking: Accomplished through template matching and deep learning approaches for locating particles on flexible and imperfect lattices.
• 3D Classification: Built-in three-dimensional classification functions for processing subtomograms.
• Integration of Common Packages: Integrates commonly used packages to streamline the cryoET and subtomogram averaging pipeline.
• Hierarchical File Organization: Organizes data hierarchically to facilitate efficient data management for large cryoET datasets.

Scientific Applications:

• Virus-like Particles: Demonstrates efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures.
• Bacterial Surface Layers: Applied to bacterial surface layers within cellular lamellae for high-resolution in situ structure determination.
• Membrane Protein Complexes: Used for membranes decorated with nuclear egress protein complexes to achieve high-resolution 3D structures.

Methodology:

Automatic particle picking uses template matching and deep learning. The pipeline includes 3D classification and integrates commonly used packages for subtomogram averaging of structures in 1D, 2D, or 3D arrays.