Q-SFD, a QUBO formulation for simultaneous fragment docking with an added inter-fragment distance term, approximately doubles top-1 recovery of reconstruction-feasible pose pairs and places at least one feasible pair in the top-5 for over 90% of benchmark cases without losing pose accuracy.
Harnessing the power of micro scopy images to accelerate drug discovery: what are the possibilities? Exp ert Opinion on Drug Discovery
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DINO-based ViT models pretrained on HPA FOV achieve macro F1 of 0.822 zero-shot and 0.860 after fine-tuning for protein localization on OpenCell, demonstrating effective transfer from SSL pretraining.
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Simultaneous Fragment Docking for Geometrically Linkable Pose Pairs
Q-SFD, a QUBO formulation for simultaneous fragment docking with an added inter-fragment distance term, approximately doubles top-1 recovery of reconstruction-feasible pose pairs and places at least one feasible pair in the top-5 for over 90% of benchmark cases without losing pose accuracy.
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Using Deep Learning Models Pretrained by Self-Supervised Learning for Protein Localization
DINO-based ViT models pretrained on HPA FOV achieve macro F1 of 0.822 zero-shot and 0.860 after fine-tuning for protein localization on OpenCell, demonstrating effective transfer from SSL pretraining.