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Found 2 papers, 1 papers with code
FlexVDW: A machine learning approach to account for protein flexibility in ligand docking
Here we present a deep learning model trained to take receptor flexibility into account implicitly when predicting van der Waals energy.
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property Prediction
However, many important molecular properties depend on complex molecular characteristics -- such as the various 3D geometries a molecule may adopt or the types of chemical interactions it can form -- that are not explicitly encoded in the feature space and must be approximated from low amounts of data.
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