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datamol-io/molfeat

0
View on GitHub↗
230 stars·30 forks·Python·Apache-2.0·8 viewsmolfeat.datamol.io↗

Molfeat

molfeat - the hub for all your molecular featurizers Docs | Homepage

Features

  • General Tools - Hub for molecular featurizers and pretrained representations.

Star history

Star history chart for datamol-io/molfeatStar history chart for datamol-io/molfeat

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Molfeat

These projects share indexed features with Molfeat. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • divelab/airsdivelab avatar

    divelab/AIRS

    780View on GitHub↗

    license-image:https://img.shields.io/badge/license-GPL3.0-green.svg license-url:https://github.com/divelab/AIRS/blob/main/LICENSE contributing-image:https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat

    Jupyter Notebook
    View on GitHub↗780
  • dralgroup/mlatomdralgroup avatar

    dralgroup/mlatom

    148View on GitHub↗

    ](https://pepy.tech/project/mlatom)

    Python
    View on GitHub↗148
  • libatoms/quiplibAtoms avatar

    libAtoms/QUIP

    396View on GitHub↗

    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…

    Fortran
    View on GitHub↗396
  • deepchem/deepchemdeepchem avatar

    deepchem/deepchem

    6,545View on GitHub↗

    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

    Pythonbiologydeep-learningdrug-discovery
    View on GitHub↗6,545
Compare all 11 related projects→

Frequently asked questions

What does datamol-io/molfeat do?

molfeat - the hub for all your molecular featurizers Docs | Homepage

What are the main features of datamol-io/molfeat?

The main features of datamol-io/molfeat are: General Tools.

Which projects share features with datamol-io/molfeat?

Projects with overlapping indexed features include: 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… pycroscopy/atomai — AtomAI is a Pytorch-based package for deep and machine learning analysis of microscopy data that doesn't require any…