Artificial intelligence in reaction prediction and chemical synthesis

Predicting Chemical Reaction Outcomes: A Grammar Ontology‐based Transformer Framework

(2021) Vipul Mann et al.   AICHE JOURNAL

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

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

Substructure-based neural machine translation for retrosynthetic prediction

(2021) Umit V. Ucak et al.   Journal of Cheminformatics

Discovery of novel chemical reactions by deep generative recurrent neural network

(2021) William Bort et al.   Scientific Reports

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

(2021) Xiaorui Wang et al.   CHEMICAL ENGINEERING JOURNAL

What Does the Machine Learn? Knowledge Representations of Chemical Reactivity

(2020) Joshua A. Kammeraad et al.   Journal of Chemical Information and Modeling

Context Aware Data-Driven Retrosynthetic Analysis

(2020) Christos A. Nicolaou et al.   Journal of Chemical Information and Modeling

Transfer Learning: Making Retrosynthetic Predictions Based on a Small Chemical Reaction Dataset Scale to a New Level

(2020) Renren Bai et al.   MOLECULES

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

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

Enhancing Retrosynthetic Reaction Prediction with Deep Learning using Multiscale Reaction Classification

(2019) Javier L. Baylon et al.   Journal of Chemical Information and Modeling

A retrosynthetic analysis algorithm implementation

(2019) Ian A. Watson et al.   Journal of Cheminformatics

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

Randomized SMILES strings improve the quality of molecular generative models

(2019) Josep Arús-Pous et al.   Journal of Cheminformatics

Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks

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

Chemical product design – recent advances and perspectives

(2019) Lei Zhang et al.   Current Opinion in Chemical Engineering

Finding the K best synthesis plans

(2018) Rolf Fagerberg et al.   Journal of Cheminformatics

Planning chemical syntheses with deep neural networks and symbolic AI

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

The promise of artificial intelligence in chemical engineering: Is it here, finally?

(2018) Venkat Venkatasubramanian   AICHE JOURNAL

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

Prediction of Organic Reaction Outcomes Using Machine Learning

(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

Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry

(2012) Mikołaj Kowalik et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Purdue Ontology for Pharmaceutical Engineering: Part I. Conceptual Framework

(2010) Leaelaf Hailemariam et al.   Journal of Pharmaceutical Innovation

Purdue Ontology for Pharmaceutical Engineering: Part II. Applications

(2010) Leaelaf Hailemariam et al.   Journal of Pharmaceutical Innovation

Route Designer: A Retrosynthetic Analysis Tool Utilizing Automated Retrosynthetic Rule Generation

(2009) James Law et al.   Journal of Chemical Information and Modeling

The 'wired' universe of organic chemistry

(2009) Bartosz A. Grzybowski et al.   Nature Chemistry