Recent advances in deep learning for retrosynthesis

Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks

(2022) Philipp Seidl et al.   Journal of Chemical Information and Modeling

AI-Driven Synthetic Route Design Incorporated with Retrosynthesis Knowledge

(2022) Shoichi Ishida et al.   Journal of Chemical Information and Modeling

Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki–Miyaura Coupling

(2022) Wiktor Beker et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Artificial Intelligence for Retrosynthesis Prediction

(2022) Yinjie Jiang et al.   Engineering

Valid, Plausible, and Diverse Retrosynthesis Using Tied Two-Way Transformers with Latent Variables

(2021) Eunji Kim et al.   Journal of Chemical Information and Modeling

Knowledge Graph Embedding for Link Prediction

(2021) Andrea Rossi et al.   ACM Transactions on Knowledge Discovery from Data

Graph neural networks for automated de novo drug design

(2021) Jiacheng Xiong et al.   DRUG DISCOVERY TODAY

Mining Toxicity Information from Large Amounts of Toxicity Data

(2021) Zhenxing Wu et al.   JOURNAL OF MEDICINAL CHEMISTRY

Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

(2021) Philippe Schwaller et al.   Science Advances

RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions

(2021) Xiaorui Wang et al.   CHEMICAL ENGINEERING JOURNAL

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

(2021) Mikołaj Sacha et al.   Journal of Chemical Information and Modeling

Deep learning in retrosynthesis planning: datasets, models and tools

(2021) Jingxin Dong et al.   BRIEFINGS IN BIOINFORMATICS

Retrosynthesis prediction using grammar-based neural machine translation: An information-theoretic approach

(2021) Vipul Mann et al.   COMPUTERS & CHEMICAL ENGINEERING

The Open Reaction Database

(2021) Steven M. Kearnes et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Molecular graph enhanced transformer for retrosynthesis prediction

(2021) Kelong Mao et al.   NEUROCOMPUTING

Artificial intelligence in reaction prediction and chemical synthesis

(2021) Venkat Venkatasubramanian et al.   Current Opinion in Chemical Engineering

Exploring chemical space using natural language processing methodologies for drug discovery

(2020) Hakime Öztürk et al.   DRUG DISCOVERY TODAY

Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018

(2020) Olivier J. Wouters et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

A review on the long short-term memory model

(2020) Greg Van Houdt et al.   ARTIFICIAL INTELLIGENCE REVIEW

Applications of link prediction in social networks: A review

(2020) Nur Nasuha Daud et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning

(2020) Michael E. Fortunato et al.   Journal of Chemical Information and Modeling

A review of the application of deep learning in medical image classification and segmentation

(2020) Lei Cai et al.   Annals of Translational Medicine

Bayesian Algorithm for Retrosynthesis

(2020) Zhongliang Guo et al.   Journal of Chemical Information and Modeling

Computational planning of the synthesis of complex natural products

(2020) Barbara Mikulak-Klucznik et al.   NATURE

The importance of synthetic chemistry in the pharmaceutical industry

(2019) Kevin R. Campos et al.   SCIENCE

RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application

(2019) Connor W. Coley et al.   Journal of Chemical Information and Modeling

Learning Retrosynthetic Planning through Simulated Experience

(2019) John S. Schreck et al.   ACS Central Science

A robotic platform for flow synthesis of organic compounds informed by AI planning

(2019) Connor W. Coley et al.   SCIENCE

Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction

(2019) Philippe Schwaller et al.   ACS Central Science

Prediction and Interpretable Visualization of Retrosynthetic Reactions Using Graph Convolutional Networks

(2019) Shoichi Ishida et al.   Journal of Chemical Information and Modeling

Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks

(2019) Shuangjia Zheng et al.   Journal of Chemical Information and Modeling

The rise of deep learning in drug discovery

(2018) Hongming Chen et al.   DRUG DISCOVERY TODAY

SCScore: Synthetic Complexity Learned from a Reaction Corpus

(2018) Connor W. Coley et al.   Journal of Chemical Information and Modeling

Organic synthesis provides opportunities to transform drug discovery

(2018) David C. Blakemore et al.   Nature Chemistry

Computational Chemical Synthesis Analysis and Pathway Design

(2018) Fan Feng et al.   Frontiers in Chemistry

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

(2018) David Silver et al.   SCIENCE

Using Machine Learning To Predict Suitable Conditions for Organic Reactions

(2018) Hanyu Gao et al.   ACS Central Science

Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction

(2017) Youjun Xu et al.   Journal of Chemical Information and Modeling

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

(2017) Bowen Liu et al.   ACS Central Science

Computer-Assisted Retrosynthesis Based on Molecular Similarity

(2017) Connor W. Coley et al.   ACS Central Science

Computer-Assisted Synthetic Planning: The End of the Beginning

(2016) Sara Szymkuć et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

The Evolution of Computing: AlphaGo

(2016) Jim X. Chen   COMPUTING IN SCIENCE & ENGINEERING

A renaissance of neural networks in drug discovery

(2016) Igor I. Baskin et al.   Expert Opinion on Drug Discovery

What’s What: The (Nearly) Definitive Guide to Reaction Role Assignment

(2016) Nadine Schneider et al.   Journal of Chemical Information and Modeling

Human-level control through deep reinforcement learning

(2015) Volodymyr Mnih et al.   NATURE

jvenn: an interactive Venn diagram viewer

(2014) Philippe Bardou et al.   BMC BIOINFORMATICS

A Survey of Monte Carlo Tree Search Methods

(2012) Cameron B. Browne et al.   IEEE Transactions on Computational Intelligence and AI in Games

Extended-Connectivity Fingerprints

(2010) David Rogers et al.   Journal of Chemical Information and Modeling

The rise of fragment-based drug discovery

(2009) Christopher W. Murray et al.   Nature Chemistry