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

Chemist Ex Machina: Advanced Synthesis Planning by Computers

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Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions

(2021) Michael R. Maser et al.   Journal of Chemical Information and Modeling

Bayesian reaction optimization as a tool for chemical synthesis

(2021) Benjamin J. Shields et al.   NATURE

Predicting Reaction Yields via Supervised Learning

(2021) Andrzej M. Żurański et al.   ACCOUNTS OF CHEMICAL RESEARCH

Scaffold‐directed face selectivity Machine‐Learned from vectors of non‐covalent interactions

(2021) Martyna Moskal et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Is organic chemistry really growing exponentially?

(2021) Sara Szymkuc et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Best practices in machine learning for chemistry

(2021) Nongnuch Artrith et al.   Nature Chemistry

Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints

(2021) Su-Yong Bae et al.   Computational Toxicology

Improved protein structure prediction using potentials from deep learning

(2020) Andrew W. Senior et al.   NATURE

Predicting Regioselectivity in Radical C−H Functionalization of Heterocycles through Machine Learning

(2020) Xin Li et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Application of Palladium Based Precatalytic Systems in the Suzuki‐Miyaura Cross‐Coupling Reactions of Chloro‐ Heterocycles

(2020) Savitha Bhaskaran et al.   ChemistrySelect

Computational planning of the synthesis of complex natural products

(2020) Barbara Mikulak-Klucznik et al.   NATURE

Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates

(2020) Giorgio Pesciullesi et al.   Nature Communications

Analyzing Learned Molecular Representations for Property Prediction

(2019) Kevin Yang et al.   Journal of Chemical Information and Modeling

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

(2019) Connor W. Coley et al.   SCIENCE

Synergy Between Expert and Machine-Learning Approaches Allows for Improved Retrosynthetic Planning

(2019) Tomasz Badowski et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Rapid and Accurate Prediction of pKa Values of C–H Acids Using Graph Convolutional Neural Networks

(2019) Rafał Roszak et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

(2018) Sabrina Jaeger et al.   Journal of Chemical Information and Modeling

Predicting reaction performance in C–N cross-coupling using machine learning

(2018) Derek T. Ahneman et al.   SCIENCE

A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow

(2018) Damith Perera et al.   SCIENCE

Efficient Syntheses of Diverse, Medicinally Relevant Targets Planned by Computer and Executed in the Laboratory

(2018) Tomasz Klucznik et al.   Chem

Planning chemical syntheses with deep neural networks and symbolic AI

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

Prediction of Major Regio-, Site-, and Diastereoisomers in Diels-Alder Reactions by Using Machine-Learning: The Importance of Physically Meaningful Descriptors

(2018) Wiktor Beker et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Comment on “Predicting reaction performance in C–N cross-coupling using machine learning”

(2018) Kangway V. Chuang et al.   SCIENCE

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

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?

(2017) G. Skoraczyński et al.   Scientific Reports

Computer-Assisted Synthetic Planning: The End of the Beginning

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

A Priori Estimation of Organic Reaction Yields

(2015) Fateme S. Emami et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

ZINC 15 – Ligand Discovery for Everyone

(2015) Teague Sterling et al.   Journal of Chemical Information and Modeling

Synthesis of many different types of organic small molecules using one automated process

(2015) J. Li et al.   SCIENCE

Selection of boron reagents for Suzuki–Miyaura coupling

(2013) Alastair J. J. Lennox et al.   CHEMICAL SOCIETY REVIEWS

Estimating chemical reactivity and cross-influence from collective chemical knowledge

(2012) Siowling Soh et al.   Chemical Science

A Positive and Unlabeled Learning Algorithm for One-Class Classification of Remote-Sensing Data

(2010) Wenkai Li et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Extended-Connectivity Fingerprints

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

A New Palladium Precatalyst Allows for the Fast Suzuki−Miyaura Coupling Reactions of Unstable Polyfluorophenyl and 2-Heteroaryl Boronic Acids

(2010) Tom Kinzel et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Synthetic popularity reflects chemical reactivity

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