1.
IUCrJ
; 10(Pt 4): 487-496, 2023 Jul 01.
Artigo
em Inglês
| MEDLINE
| ID: mdl-37409806
RESUMO
The 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.