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Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms
2020
PLoS Computational Biology
Cryo-electron tomography (cryo-ET) provides 3D visualization of subcellular components in the near-native state and at sub-molecular resolutions in single cells, demonstrating an increasingly important role in structural biology in situ. However, systematic recognition and recovery of macromolecular structures in cryo-ET data remain challenging as a result of low signal-to-noise ratio (SNR), small sizes of macromolecules, and high complexity of the cellular environment. Subtomogram structural
doi:10.1371/journal.pcbi.1008227
pmid:33175839
fatcat:4zwm6iz7ijhr5ajtmj3bhf42zu