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Found 4 papers, 2 papers with code
TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design
Searching the vast chemical space for drug-like and synthesizable molecules with high binding affinity to a protein pocket is a challenging task in drug discovery.
All SMILES Variational Autoencoder for Molecular Property Prediction and Optimization
Variational autoencoders (VAEs) defined over SMILES string and graph-based representations of molecules promise to improve the optimization of molecular properties, thereby revolutionizing the pharmaceuticals and materials industries.
All SMILES Variational Autoencoder
Variational autoencoders (VAEs) defined over SMILES string and graph-based representations of molecules promise to improve the optimization of molecular properties, thereby revolutionizing the pharmaceuticals and materials industries.
Ranked #1 on
Molecular Graph Generation
on ZINC
(QED Top-3 metric)
PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction
In silico drug-target interaction (DTI) prediction is an important and challenging problem in biomedical research with a huge potential benefit to the pharmaceutical industry and patients.
