STOPGAP, an open-source package for template matching, subtomogram alignment, and classification.
William WanSagar KhavnekarJonathan WagnerPublished in: bioRxiv : the preprint server for biology (2023)
Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections, and in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species, and classifying different conformational states. Here we describe STOPGAP, an open-source package for subtomogram averaging designed to provide users with fine control over each of these steps. In providing detailed descriptions of the image processing algorithms that STOPGAP uses, we intend for this manuscript to also serve as a technical resource to users as well as further community-driven software development.
Keyphrases
- high resolution
- single molecule
- deep learning
- electron microscopy
- machine learning
- mass spectrometry
- molecular dynamics
- molecular dynamics simulations
- induced apoptosis
- healthcare
- mental health
- sars cov
- air pollution
- big data
- tandem mass spectrometry
- cell cycle arrest
- genetic diversity
- endoplasmic reticulum stress
- data analysis
- social media
- simultaneous determination
- ultrasound guided