DeepChem is an open-source Python framework for applying deep learning to molecular, chemical, and biological data, serving as a comprehensive toolkit for drug discovery and materials science. At its core, it provides a featurizer-pipeline abstraction that converts raw molecular data into numerical representations, including graph-based molecular structures, SMILES tokenization vocabularies, and disk-sharded dataset persistence for handling large-scale data that exceeds RAM capacity. The framework distinguishes itself through integrated molecular docking workflows that automate pocket detecti
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molfeat - the hub for all your molecular featurizers Docs | Homepage
scikit-matter
scikit-learn-contrib/scikit-matter 的主要功能包括：General Tools。
scikit-learn-contrib/scikit-matter 的开源替代品包括： datamol-io/molfeat — molfeat - the hub for all your molecular featurizers Docs | Homepage. deepchem/deepchem — DeepChem is an open-source Python framework for applying deep learning to molecular, chemical, and biological data,… divelab/airs — [license-image]:https://img.shields.io/badge/license-GPL3.0-green.svg [license-url]:https://github.com/divelab/AIRS/blo… dralgroup/mlatom — ](https://pepy.tech/project/mlatom). libatoms/quip — The QUIP package is a collection of software tools to carry out molecular dynamics simulations. It implements a… materialyzeai/maml — maml (MAterials Machine Learning) is a Python package that aims to provide useful high-level interfaces that make ML…
