/Awesome-AI-for-Chemical-Reaction

Awesome papers related to Artificial Intelligence (AI) for Chemical Reaction.

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Awesome-AI-for-Chemical-Reaction

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Awesome papers related to Artificial Intelligence (AI) for Chemical Reaction.

Artificial Intelligence has significantly impacted the field of chemical reactions, demonstrating the potential to revolutionize traditional approaches to prediction, optimization, and synthesis tasks. To facilitate further exploration and understanding of AI's role in chemical reaction tasks, this repository offers a curated list of research papers. These selected papers highlight innovative applications of AI in chemical reactions, providing a comprehensive resource for those interested in the cutting-edge intersection of AI and chemical reactions.

This repository is still a work in progress. Please feel free to create a pull request if you would like to add other awesome papers.

Surveys

  1. [Chemical Reviews 2021] Machine Learning for Chemical Reactions [paper]

Forward Reaction

Reaction Outcomes (Reactivity) Prediction

  1. [NeurIPS 2017] Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
  2. [Chemical Science 2018] "Found in Translation": Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models
  3. [ACS Central Science 2019] Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
  4. [Chemical Science 2019] A Graph-Convolutional Neural Network Model for the Prediction of Chemical Reactivity
  5. [Nature Machine Intelligence 2021] Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks
  6. [Chemical Science 2022] Improving Machine Learning Performance on Small Chemical Reaction Data with Unsupervised Contrastive Pretraining
  7. [ICLR 2022] Chemical-Reaction-Aware Molecule Representation Learning
  8. [ICML Workshop 2022] Pre-Training Transformers for Molecular Property Prediction Using Reaction Prediction
  9. [Machine Learning: Science and Technology 2022] Chemformer: A Pre-Trained Transformer for Computational Chemistry
  10. [Nature Machine Intelligence 2022] A Generalized-Template-Based Graph Neural Network for Accurate Organic Reactivity Prediction

Reaction Yields (Performance) Prediction

  1. [Machine Learning: Science and Technology 2021] Prediction of Chemical Reaction Yields Using Deep Learning
  2. [Journal of Cheminformatics 2022] Uncertainty-Aware Prediction of Chemical Reaction Yields with Graph Neural Networks
  3. [Nature Communications 2023] Reaction Performance Prediction with an Extrapolative and Interpretable Graph Model Based on Chemical Knowledge

Reaction Conditions Prediction

  1. [ACS Central Science 2018] Using Machine Learning To Predict Suitable Conditions for Organic Reactions

Reaction Mechanism

  1. [ICLR 2019] A Generative Model For Electron Paths
  2. [Nature Communications 2020] Machine Learning in Chemical Reaction Space [paper] [code]

Reaction Classification

  1. [ICLR 2022] Chemical-Reaction-Aware Molecule Representation Learning

Reaction Optimization

  1. [Chemical Reviews] A Brief Introduction to Chemical Reaction Optimization

Transition State Generation

  1. [Nature Computational Science 2023] Accurate Transition State Generation with an Object-Aware Equivariant Elementary Reaction Diffusion Model

Enantioselectivity Prediction / Catalyst Design

  1. [Nature 2019] Holistic Prediction of Enantioselectivity in Asymmetric Catalysis
  2. [Nature Synthesis 2023] Enantioselectivity Prediction of Pallada-Electrocatalysed C–H Activation Using Transition State Knowledge in Machine Learning

Retrosynthesis

Retrosynthesis Surveys

  1. [Briefings in Bioinformatics] Deep Learning in Retrosynthesis Planning: Datasets, Models and Tools
  2. [arXiv 2023] Recent Advances in Artificial Intelligence for Retrosynthesis
  3. [Engineering 2023] Artificial Intelligence for Retrosynthesis Prediction
  4. [IJCAI 2023] A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges

Retrosynthesis Prediction

  1. [ACS Central Science 2017] Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models
  2. [ACS Central Science 2017] Computer-Assisted Retrosynthesis Based on Molecular Similarity
  3. [NeurIPS 2019] Retrosynthesis Prediction with Conditional Graph Logic Network
  4. [Journal of Chemical Information and Modeling 2020] Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks
  5. [NeurIPS 2021] Learning Graph Models for Retrosynthesis Prediction
  6. [AAAI 2023] Learning Chemical Rules of Retrosynthesis with Pre-Training

Retrosynthesis Planning

  1. [Journal of Chemical Information and Modeling 2020] Bayesian Algorithm for Retrosynthesis
  2. [Chemical Science 2020] Automatic Retrosynthetic Route Planning Using Template-Free Models
  3. [ICML 2020] Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
  4. [ChemRxiv 2023] Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multi-Step Retrosynthesis
  5. [ICLR 2024] RetroBridge: Modeling Retrosynthesis with Markov Bridges
  6. [ICLR 2024] Retro-Fallback: Retrosynthetic Planning in an Uncertain World
  7. [ICLR 2024] Active Retrosynthetic Planning Aware of Route Quality

Miscellaneous

Datasets

  1. [Journal of Medicinal Chemistry] Big Data from Pharmaceutical Patents: A Computational Analysis of Medicinal Chemists’ Bread and Butter

Reaction Role Assignment

  1. [Journal of Chemical Information and Modeling 2016] What’s What: The (Nearly) Definitive Guide to Reaction Role Assignment

Reaction Discovery

  1. [Scientific Reports] Discovery of Novel Chemical Reactions by Deep Generative Recurrent Neural Network