A deep learning solution for crystallographic structure determination

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dc.citation.firstpage487
dc.citation.issueNumber4
dc.citation.journalTitleIUCrJ
dc.citation.lastpage496
dc.citation.volumeNumber10
dc.contributor.authorPan, T.
dc.contributor.authorJin, S.
dc.contributor.authorMiller, M. D.
dc.contributor.authorKyrillidis, A.
dc.contributor.authorPhillips, G. N.
dc.date.accessioned2023-08-01T17:29:49Z
dc.date.available2023-08-01T17:29:49Z
dc.date.issued2023
dc.description.abstractThe general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept.
dc.identifier.citationPan, T., Jin, S., Miller, M. D., et al.. "A deep learning solution for crystallographic structure determination." <i>IUCrJ,</i> 10, no. 4 (2023) International Union of Crystallography: 487-496. https://doi.org/10.1107/S2052252523004293.
dc.identifier.digitalmf5063
dc.identifier.doihttps://doi.org/10.1107/S2052252523004293
dc.identifier.urihttps://hdl.handle.net/1911/115045
dc.language.isoeng
dc.publisherInternational Union of Crystallography
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license.  Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of Fair Use or other exemptions to copyright law must be obtained from the copyright holder.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleA deep learning solution for crystallographic structure determination
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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