Cryo-electron tomography, combined with subtomogram averaging (STA), can reveal three-dimensional (3D) macromolecule structures in the near-native state from cells and other biological samples. In STA, to get a high-resolution 3D view of macromolecule structures, diverse macromolecules captured by the cellular tomograms need to be accurately classified. However, due to the poor signal-to-noise-ratio (SNR) and severe ray artifacts in the tomogram, it remains a major challenge to classify macromolecules with high accuracy.

中文翻译：

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低温电子层析成像中具有3D膨胀致密网络的大分子结构分类。

低温电子断层扫描与子图平均（STA）相结合，可以从细胞和其他生物样品中以接近自然状态显示三维（3D）高分子结构。在STA中，要获得大分子结构的高分辨率3D视图，需要对细胞断层图捕获的各种大分子进行准确分类。但是，由于断层图像中较差的信噪比（SNR）和严重的射线伪​​影，因此，对大分子进行高精度分类仍然是一项重大挑战。