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Found 7 papers, 3 papers with code
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+
Uni-Mol+ first generates a raw 3D molecule conformation from inexpensive methods such as RDKit.
Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decoder
Dense retrieval requires high-quality text sequence embeddings to support effective search in the representation space.
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder
Dense retrieval requires high-quality text sequence embeddings to support effective search in the representation space.
3D Molecular Generation via Virtual Dynamics
Extensive experiment results on pocket-based molecular generation demonstrate that VD-Gen can generate novel 3D molecules to fill the target pocket cavity with high binding affinities, significantly outperforming previous baselines.
Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking?
What's more, they claim to perform better than traditional molecular docking, but the approach of comparison is not fair, since traditional methods are not designed for docking on the whole protein without a given pocket.
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction
XtalNet represents a significant advance in CSP, enabling the prediction of complex structures from PXRD data without the need for external databases or manual intervention.
Multi-level protein pre-training with Vabs-Net
In recent years, there has been a surge in the development of 3D structure-based pre-trained protein models, representing a significant advancement over pre-trained protein language models in various downstream tasks.
