A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactions" (https://advances.sciencemag.org/content/7/15/eabe4166).

A lightweight python-only library for reading and writing SMILES strings

DeepSMILES - A variant of SMILES for use in machine-learning

SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT, SLICES-PLUS

The repository contains the network and the related scripts for encoder-decoder based Chemical Image Recognition

Draw molecules with plotly!

PyTorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

⚗️ An all-in-one solution for chemical property retrieval from PubChem.

pytoda - PaccMann PyTorch Dataset Classes. Read the docs: https://paccmann.github.io/paccmann_datasets/

Implementation of the paper "Neuraldecipher - Reverse-engineering extended-connectivity fingerprints (ECFPs) to their molecular structures" by Tuan Le, Robin Winter, Frank Noé and Djork-Arné Clevert

3D diverse conformers generation using rdkit

Extract Molecular SMILES embeddings from language models pre-trained with various objectives architectures.

Automated BigSMILES conversion workflow and dataset for homopolymeric macromolecules

A tool to convert IUPAC representations of glycans into SMILES strings.

Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow

A recurrent neural network (RNN) that generates drug-like molecules for drug discovery.

A Python library for efficient manipulation, conformer optimization, and molecular structure data.

A collection of deep reinforcement learning-based & GFlowNet drug molecule generators focused on generation of molecules using Graphs/SELFIES guided by modern retrosynthesis tools to increase synthetic accessibility of de-novo designed drugs.

Low code molecular property prediction