Awesome
<h1 align="center"> <br> <a href="https://github.com/Kohulan/Smiles-TO-iUpac-Translator"><img src="https://github.com/Kohulan/Smiles-TO-iUpac-Translator/blob/development/docs/_static/STOUT.png?raw=true" alt="STOUT Logo" width="400"></a> <br> STOUT V2.0 <br> </h1> <h4 align="center">Smiles TO iUpac Translator: Advanced Chemical Nomenclature Translation</h4> <p align="center"> <a href="https://opensource.org/licenses/MIt"> <img src="https://img.shields.io/badge/License-MIT%202.0-blue.svg" alt="License"> </a> <a href="https://github.com/Kohulan/Smiles-TO-iUpac-Translator/graphs/commit-activity"> <img src="https://img.shields.io/badge/Maintained%3F-yes-blue.svg" alt="Maintenance"> </a> <a href="https://github.com/Kohulan/Smiles-TO-iUpac-Translator/actions/workflows/Check_errors.yml"> <img src="https://github.com/Kohulan/Smiles-TO-iUpac-Translator/actions/workflows/Check_errors.yml/badge.svg" alt="Workflow"> </a> <br> <a href="https://GitHub.com/Kohulan/Smiles-TO-iUpac-Translator/issues/"> <img src="https://img.shields.io/github/issues/Kohulan/Smiles-TO-iUpac-Translator.svg" alt="GitHub issues"> </a> <a href="https://GitHub.com/Kohulan/Smiles-TO-iUpac-Translator/graphs/contributors/"> <img src="https://img.shields.io/github/contributors/Kohulan/Smiles-TO-iUpac-Translator.svg" alt="GitHub contributors"> </a> <a href="https://www.tensorflow.org"> <img src="https://img.shields.io/badge/TensorFlow-2.15.0-FF6F00.svg?style=flat&logo=tensorflow" alt="tensorflow"> </a> <br> <a href="https://GitHub.com/Kohulan/Smiles-TO-iUpac-Translator/releases/"> <img src="https://img.shields.io/github/release/Kohulan/Smiles-TO-iUpac-Translator.svg" alt="GitHub release"> </a> <a href="https://pypi.org/project/STOUT-pypi/"> <img src="https://badge.fury.io/py/STOUT-pypi.svg" alt="PyPI version"> </a> <a href="https://pypi.org/project/STOUT-pypi/"> <img src="https://img.shields.io/pypi/pyversions/STOUT-pypi.svg" alt="Python versions"> </a> <a href="https://doi.org/10.5281/zenodo.13318286"> <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.13318286.svg" alt="DOI"> </a> </p> <p align="center"> <a href="#key-features">Key Features</a> • <a href="#installation">Installation</a> • <a href="#how-to-use">How To Use</a> • <a href="#training-stout">Training STOUT</a> • <a href="#acknowledgements">Acknowledgements</a> • <a href="#citation">Citation</a> </p> <p align="center"> <img src="https://github.com/Kohulan/Smiles-TO-iUpac-Translator/raw/master/docs/_static/STOUT_demo.gif" alt="STOUT Demo"> </p>Key Features
- 🧪 Translate SMILES to IUPAC names
- 🔬 Convert IUPAC names back to valid SMILES strings
- 🤖 Powered by advanced transformer models
- 💻 Cross-platform support (Linux, macOS, Windows via Ubuntu shell)
- 🚀 High-performance chemical nomenclature translation
- 🧠 Training code available for custom model development
Installation
Choose your preferred installation method:
<details> <summary><b>📦 PyPI Installation</b></summary>pip install STOUT-pypi
conda create --name STOUT python=3.10
conda activate STOUT
conda install -c decimer stout-pypi
pip install git+https://github.com/Kohulan/Smiles-TO-iUpac-Translator.git
How To Use
from STOUT import translate_forward, translate_reverse
# SMILES to IUPAC name translation
SMILES = "CN1C=NC2=C1C(=O)N(C(=O)N2C)C"
IUPAC_name = translate_forward(SMILES)
print(f"🧪 IUPAC name of {SMILES} is: {IUPAC_name}")
# IUPAC name to SMILES translation
IUPAC_name = "1,3,7-trimethylpurine-2,6-dione"
SMILES = translate_reverse(IUPAC_name)
print(f"🔬 SMILES of {IUPAC_name} is: {SMILES}")
Training STOUT
For researchers interested in training their own STOUT models or understanding the training process, we provide the training code in a separate repository:
This repository contains the necessary scripts and instructions for training STOUT models. Please note that training requires significant computational resources and a large dataset. Refer to the README in the training repository for detailed instructions.
Model Card
Rajan, K., Steinbeck, C., & Zielesny, A. (2024). STOUT V2 - Model library (Version v3). Zenodo. https://doi.org/10.5281/zenodo.13318286
Model Use
- Primary intended uses: Translation between SMILES and IUPAC names for chemical compounds
- Primary intended users: Chemists, researchers, and developers in the field of cheminformatics
- Out-of-scope use cases: Not intended for critical applications where 100% accuracy is required
Acknowledgements
<p align="center"> Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC) <br><br> <img src="https://user-images.githubusercontent.com/30716951/220350828-913e6645-6a0a-403c-bcb8-160d061d4606.png" width="200"> </p> <h2 align="center">Part of the DECIMER Project</h2> <p align="center"> <a href="https://decimer.ai"> <img src="https://github.com/Kohulan/DECIMER-Image-to-SMILES/raw/master/assets/DECIMER.gif" alt="DECIMER Logo" width="400"> </a> </p> <h2 align="center">About Us</h2> <p align="center"> <a href="https://cheminf.uni-jena.de"> <img src="https://github.com/Kohulan/DECIMER-Image-to-SMILES/blob/master/assets/CheminfGit.png?raw=true" alt="Cheminformatics and Computational Metabolomics Group" width="300"> </a> </p>Citation
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Rajan, K., Zielesny, A. & Steinbeck, C. STOUT: SMILES to IUPAC names using neural machine translation. J Cheminform 13, 34 (2021). https://doi.org/10.1186/s13321-021-00512-4
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Rajan K, Zielesny A, Steinbeck C. STOUT V2.0: SMILES to IUPAC name conversion using transformer models. ChemRxiv. 2024; https://doi.org/10.26434/chemrxiv-2024-089vs
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