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computational-chemistryresearch

deepchem

Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.

lamm-mit
maintainer
lamm-mit
Mis à jour 3/14/2026
Étoiles
156
Forks
35
quick start

Installation and usage

Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.

Installation
$ install --globalskills.sh
Utilisation

Après l'installation, vous pouvez utiliser ce skill en exécutant la commande suivante dans votre terminal :

skills use deepchem