A tool for retrosynthetic planning

Tools to train synthesis prediction models

ADVANCED ANALYST :: Foundations for Advanced Data Analytics in R

Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search

Utilities for working with datasets of chemical reactions, reaction templates and template extraction.

Machine Learning School

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

The fastai book, published as Jupyter Notebooks

Home of the PaRoutes framework for benchmarking multi-step retrosynthesis predictions.

RetroExplainer: A chemical knowledge and deep-leaning guided molecular assembly approach for retrosynthesis prediction with quantitative interpretability

The simplest, fastest repository for training/finetuning medium-sized GPTs.

EPFL CH-457 "AI for chemistry"

Wrapper for RDKit's RunReactants to improve stereochemistry handling

This repo contains ReactionDataExtractor v.2 - software toolkit for extraction of information from chemical reaction schemes

RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactio…

Revised breaking of retrosynthetically interesting chemical substructures (r-BRICS) – a revised BRICS module based on rdKit that breaks ring structures and carbon chains

Multi-Step Retrosynthesis Tool based on Augmented Disconnection Aware Triple Transformer Loop Predictions

Introduction to R programming and mathematical statistics for bioinformatics and biomedical sciences.

Neural Networks: Zero to Hero

Calculate Böttcher score on small molecules (doi.org/10.1021/acs.jcim.5b00723)

Code for "Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits"

DATA SCIENCE SESSIONS :: Introduction to R for Data Science

Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search

SMILES enumeration for QSAR modelling using LSTM recurrent neural networks

Use convolutional neural net to detect segment and classify material phases and vessels in chemistry lab and other setting involving materials in mostly transparent vessels

Extraction and re-use(ability) of chemical information from common scientific documents containing ChemDraw files