NucleoFind: A Deep-Learning Network for Interpreting Nucleic Acid Electron Density

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Nucleic acid electron density interpretation remains a difficult problem for computer programs to deal with. Programs tend to rely on exhaustive searches to recognise characteristic features. NucleoFind is a deep-learning-based approach to interpreting and segmenting electron density. Using a crystallographic map, the positions of the phosphate group, sugar ring and nitrogenous base group are able to be predicted with high accuracy.

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If you find NucleoFind useful, please cite:

  • Jordan S Dialpuri, Jon Agirre, Kathryn D Cowtan, Paul S Bond, NucleoFind: A Deep-Learning Network for Interpreting Nucleic Acid Electron Density, Nucleic Acid Research, 2024 https://doi.org/10.1093/nar/gkae715

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BLAKE2b-256 f5a7e899ae39654db893daf61473acff5c4c1cf56460fcd076acd5a6ac1e8c3d

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