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Point transformer for protein structural heterogeneity analysis using CryoEM

arXiv 2601.18713 ↗First posted 26 Jan 2026q-bio.QM cs.AIcited by 0

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Abstract (arXiv)

Structural dynamics of macromolecules is critical to their structural-function relationship. Cryogenic electron microscopy (CryoEM) provides snapshots of vitrified protein at different compositional and conformational states, and the structural heterogeneity of proteins can be characterized through computational analysis of the images. For protein systems with multiple degrees of freedom, it is still challenging to disentangle and interpret the different modes of dynamics. Here, by implementing Point Transformer, a self-attention network designed for point cloud analysis, we are able to improve the performance of heterogeneity analysis on CryoEM data, and characterize the dynamics of highly complex protein systems in a more human-interpretable way.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 22 references that are in the map. First posted on arXiv 26 Jan 2026.

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References · 4

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
  4. 2020Point Transformercited by 1,470

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