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Article . 2023
License: CC BY
Data sources: Datacite
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Article . 2023
License: CC BY
Data sources: ZENODO
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De novo structure modeling for nucleic acids in cryo-EM maps using deep learning

Authors: Wang, Xiao; Terashi, Genki; Kihara, Daisuke;

De novo structure modeling for nucleic acids in cryo-EM maps using deep learning

Abstract

Here, we store the detection results and modeled structures generated by CryoREAD for its testing dataset, consisting of 68 maps. Results from different EM-Maps are saved in sub-directories with the name [EMD-ID]. In each subfolder, the modeled structures are saved in [EMD-ID].pdb format, while the detection results are saved in the "2nd_stage_detection" directory. Specifically, we keep the detection outputs of our 2nd stage network, which include the probabilities of phosphate, sugar, base, protein, and the individual bases A, U/T, C, and G. If you used CryoREAD, please cite: "Xiao Wang, Genki Terashi & Daisuke Kihara. De novo structure modeling for nucleic acids in cryo-EM maps using deep learning. bioArxiv, 2022."

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Keywords

cryo-EM, deep learning, DNA/RNA, Structure Modeling

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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