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Creators/Authors contains: "Pan, Tom"

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  1. ; ; ; ; (, IUCrJ)
    Moffat, K (Ed.)
    The generalde novosolution 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. 
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