Retrosynthesis prediction for organic molecules with LocalRetro
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Updated
Jan 27, 2026 - Jupyter Notebook
Retrosynthesis prediction for organic molecules with LocalRetro
RetroExplainer: A chemical knowledge and deep-leaning guided molecular assembly approach for retrosynthesis prediction with quantitative interpretability
Learning Graph Models for Retrosynthesis Prediction (NeurIPS 2021)
Computer-aided synthesis planning
Source code and documentation of a computer assisted synthesis planning (CASP) tool used for the analysis of reaction datasets.
RetroBridge: Markov Bridge Model for Retrosynthesis Planning
Energy-based modeling of chemical reactions
Multi-Step Retrosynthesis Tool based on Augmented Disconnection Aware Triple Transformer Loop Predictions
RetroCast: A Unified Format for Multistep Retrosynthesis
A repository for evaluating single-step retrosynthesis algorithms
Preprocessing of datasets of chemical reactions: standardization, filtering, augmentation, tokenization, etc.
An Interactive Platform for Visualizing and Comparing Retrosynthetic Routes
PydanticAI Agent for chemistry related tasks including the retrosynthesis of chemical compounds.
Supporting code for the "Autonomous retrosynthesis of gold nanoparticles via spectral shape matching" paper. DOI : 10.1039/D2DD00025C
A web application to display the retrosynthetic reaction pathway using FLASK
From molecule to manufacturing: retrosynthesis, process engineering, cost estimation, and safety analysis. Pure Python, no RDKit required.
The NeoChemSynthWave: Data project.
This project is an ML-based retrosynthesis tool predicting reactants from chemical structures, with an interactive Streamlit interface for molecule input, visualization, and stepwise reaction exploration.
Organic Synthesis AI Assistant is a desktop application designed for organic chemists to revolutionize how synthesis routes are planned. Powered by cutting-edge AI, this tool assists researchers and scientists in crafting efficient and innovative synthesis strategies for complex molecules.
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