Predicting the performance of automated crystallographic model-building pipelines

Alharbi, Emad, Bond, Paul orcid.org/0000-0002-8465-4823, Calinescu, Radu orcid.org/0000-0002-2678-9260 et al. (1 more author) (2021) Predicting the performance of automated crystallographic model-building pipelines. Acta crystallographica. Section D, Structural biology. pp. 1591-1601. ISSN 2059-7983

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Authors/Creators:
Dates:
  • Accepted: 10 October 2021
  • Published: 1 December 2021
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
The University of York > Faculty of Sciences (York) > Chemistry (York)
Funding Information:
FunderGrant number
BBSRCBB/S005099/1
Depositing User: Pure (York)
Date Deposited: 08 Dec 2021 17:30
Last Modified: 07 Dec 2022 16:07
Published Version: https://doi.org/10.1107/S2059798321010500
Status: Published
Refereed: Yes
Identification Number: https://doi.org/10.1107/S2059798321010500

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Description: Predicting the performance of automated crystallographic model-building pipelines

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