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A deep learning-based method for modeling of RNA structures from cryo-EM maps

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We developed a deep learning-based method, EMRNA, to automatically model RNA structures from cryo-electron microscopy maps. Evaluation of EMRNA on diverse test sets of RNA maps shows that it builds RNA models with high accuracy and efficiency.

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Fig. 1: EMRNA workflow and examples of built models.

References

  1. Zhang, J. et al. Advances and opportunities in RNA structure experimental determination and computational modeling. Nat. Methods 19, 1193–1207 (2022). A review that presents advances in the experimental determination and computational modeling of RNA structures.

  2. Kappel, K. et al. Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures. Nat. Methods 17, 699–707 (2020). This paper reports a method for modeling full-length RNA structures from RNA-only cryo-EM maps.

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This is a summary of: Li, T. et al. All-atom RNA structure determination from cryo-EM maps. Nat. Biotechnol. https://doi.org/10.1038/s41587-024-02149-8 (2024)

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A deep learning-based method for modeling of RNA structures from cryo-EM maps. Nat Biotechnol (2024). https://doi.org/10.1038/s41587-024-02162-x

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  • DOI: https://doi.org/10.1038/s41587-024-02162-x

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