AlphaFold as a Prior: Experimental StructureDetermination Conditioned on a Pretrained Neural Network https://www.biorxiv.org/content/10.1101/2025.02.18.638828v1

AlphaFold as a Prior: Experimental StructureDetermination Conditioned on a Pretrained Neural Network www.biorxiv.org/content/10.1101/2025.02.18.638828v1 #cryoem

AlphaFold as a Prior: Experimental StructureDetermination Conditioned on a Pretrained Neural Network [new]
AlphaFold2 aids experimental structure analysis (cryo-EM, ET, X-ray). Improves modeling of structural variations.

AlphaFold as a Prior: Experimental StructureDetermination Conditioned on a Pretrained Neural Network https://www.biorxiv.org/content/10.1101/2025.02.18.638828v1

Slice'N'Dice can address cases where the conformation of a structure prediction, especially in terms of inter-domain orientations, differs significantly from that of the target in both #crystallography and #cryoEM. #StructureDetermination doi.org/10.1107/S205...

Alexander J. Blake: The challenges of growing great crystals – or at least good enough ones! ##CrystalGrowth##CommonTechniques##StructureDetermination... ##IUCrhttps://journals.iucr.org/paper?S2053229624008416

The use of convolutional neural networks for segmentation of the initial experimental phasing electron-density maps improves current density-modification methods #ComputationalModelling #MolecularCrystals #StructureDetermination t.co/h95ASNdc51

Pavol Skubák: Deep-learning map segmentation for protein X-ray crystallographic structure determination ##ComputationalModelling##MolecularCrystals##StructureDetermination@UniLeiden...##IUCrhttps://journals.iucr.org/paper?S2059798324005217