Computational Chemistry
Showing 29 of 29 projects
A machine learning package implementing message passing neural networks for predicting molecular and reaction properties.
A curated list of awesome Python frameworks, libraries, software, and resources for chemistry and cheminformatics.
An open-source suite of ab initio quantum chemistry programs for high-accuracy molecular simulations, written in C++ with a Python driver.
WebGL-accelerated JavaScript library for interactive molecular visualization in web applications.
A curated collection of research papers on molecular and material design using generative AI and deep learning techniques.
A curated list of awesome cheminformatics software, libraries, resources, and tools, primarily command-line based and open-source.
A Python package for applying graph neural networks to molecular graphs and biological networks in life science research.
A PyTorch and TorchDrug based deep learning library for drug pair scoring, predicting interactions, side effects, and synergy.
A deep learning toolkit for computational chemistry and drug design research with PyTorch backend.
A Python library for reading, writing, and analyzing molecular dynamics trajectories with support for numerous file formats.
A deep learning library built on Chainer for molecular property prediction using graph convolutional neural networks.
A junction tree variational autoencoder for generating valid molecular graphs with desired chemical properties.
A Python library for molecular processing built on RDKit with a simple API and good defaults.
A Cookiecutter template for creating Python packages in computational molecular sciences with pre-configured CI, testing, and documentation.
A Python library for parsing computational chemistry logfiles and implementing platform-independent algorithms.
A reinforcement learning framework for de novo drug design that generates novel molecular structures with desired properties.
Official implementation of a 3D equivariant diffusion model for generating drug-like molecules that bind to specific protein targets and predicting their binding affinity.
A curated collection of papers, datasets, tools, and resources for applying machine learning to small-molecule drug discovery.
A Julia toolkit for graph-based molecule modeling, cheminformatics analysis, and chemical structure manipulation.
A high-level environment for solving integral and differential equations in many dimensions using adaptive, fast methods with guaranteed precision.
A unified framework for modeling chemically reactive systems with support for equilibrium, kinetics, and multiple thermochemical databases.
A T5-based model for bidirectional translation between molecular structures (SMILES) and natural language descriptions.
A Python wrapper for RDKit's RunReactants that improves stereochemistry handling in chemical reaction applications.
A Python package for easy molecular docking with a curated dataset and benchmark tasks for drug discovery.
A transformer-based model for unconditional and conditional molecular generation using GPT architecture trained on chemical datasets.
A conversational AI framework for editing small molecules, peptides, and proteins using retrieval-augmented generation and domain feedback.
A Java-based 2D chemical structure editor and viewer built on the Chemistry Development Kit (CDK).
An automated workflow for generating and storing DFT calculations for organic molecules.
A massively parallel quantum chemistry platform for ab initio electronic structure simulations of molecules and solids.
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