Deep residual networks for crystallography trained on synthetic data is a research paper published in Acta Crystallographica Section D Structural Biology (2024). On theSindex it has a DataRank of 0. It has been cited 4 times.
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National Institutes of Health, National Institute of General Medical Sciences
Grant: P30GM133894
National Institutes of Health, National Institute of General Medical Sciences
Grant: R01GM124149
National Institutes of Health, National Institute of General Medical Sciences
Grant: P30GM124169
National Science Foundation
Grant: 1924205
HDR DSC: Collaborative Research: Central Coast Data Science Partnership: Training a New Generation of Data Scientists
SLAC National Accelerator Laboratory
Grant: DE-AC02-76SF00515
National Institutes of Health
Grant: 2R01GM124149-06
Eliminating Critical Systematic Errors In Structural Biology With Next-Generation Simulation
National Institutes of Health
Grant: 3P30GM133894-06S1
A Synchrotron Radiation Structural Biology Resource
National Institutes of Health
Grant: 2P30GM124169-06
ALS Efficiently Networking Advanced Beam Line Experiments (ALS-ENABLE)
FWCI
0.37
Citation Percentile
0.5%
Citation Trend
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