Open-source alternatives to Atomai

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

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

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

Generic but comprehensive pipeline for prokaryotic genome annotation and interrogation with interactive reports and shiny app.

A pipeline for preprocessing NGS data from Illumina, Nanopore and PacBio technologies

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…

maml (MAterials Machine Learning) is a Python package that aims to provide useful high-level interfaces that make ML for materials science as easy as possible.

Software for intuitively doing Differential Gene Expression (DGE) analysis on Windows and GNU\Linux, based on R packages.

QML: Quantum Machine Learning

QuPath - Open-source bioimage analysis for research

The official sources for the RDKit library

scikit-matter

The JARVIS-Tools is an open-access software package for atomistic data-driven materials design. JARVIS-Tools can be used for a) setting up calculations, b) analysis and informatics, c) plotting, d) database development and e) web-page development.

MAST-ML is an open-source Python package designed to broaden and accelerate the use of machine learning in materials science research