BraggNet : integrating Bragg peaks using neural networks
Neutron crystallography offers enormous potential to complement structures from X-ray crystallography by clarifying the positions of low-Z elements, namely hydrogen. Macromolecular neutron crystallography, however, remains limited, in part owing to the challenge of integrating peak shapes from pulse...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | Journal of applied crystallography. - 1998. - 52(2019), Pt 4 vom: 01. Aug., Seite 854-863
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| 1. Verfasser: |
Sullivan, Brendan
(VerfasserIn) |
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| Weitere Verfasser: |
Archibald, Rick,
Azadmanesh, Jahaun,
Vandavasi, Venu Gopal,
Langan, Patricia S,
Coates, Leighton,
Lynch, Vickie,
Langan, Paul |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | Journal of applied crystallography
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| Schlagworte: | Journal Article
computational modelling
integration
machine learning
neural networks
neutron crystallography |
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