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
The QUIP package is a collection of software tools to carry out molecular dynamics simulations. It implements a variety of interatomic potentials and tight binding quantum mechanics, and is also able to call external packages, and serve as plugins to other software such as LAMMPS, CP2K and also…
Les fonctionnalités principales de libatoms/quip sont : General Tools.
Les alternatives open-source à libatoms/quip incluent : 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). materialyzeai/maml — maml (MAterials Machine Learning) is a Python package that aims to provide useful high-level interfaces that make ML… pycroscopy/atomai — AtomAI is a Pytorch-based package for deep and machine learning analysis of microscopy data that doesn't require any…