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The Synthesizability of Molecules Proposed by Generative Models

Journal of chemical information and modeling, 2020-12, Vol.60 (12), p.5714-5723

2020

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Autonomous Discovery in the Chemical Sciences Part I: Progress

Angewandte Chemie International Edition, 2020-12, Vol.59 (51), p.22858-22893

International ed. in English, 2020

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A graph-convolutional neural network model for the prediction of chemical reactivity

Chemical science (Cambridge), 2019-01, Vol.10 (2), p.370-377

2019

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Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability, and explainability

The Journal of chemical physics, 2022-02, Vol.156 (8), p.084104-084104

2022

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Autonomous Discovery in the Chemical Sciences Part II: Outlook

Angewandte Chemie International Edition, 2020-12, Vol.59 (52), p.23414-23436

International ed. in English, 2020

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Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

Journal of chemical information and modeling, 2020-08, Vol.60 (8), p.3770-3780

2020

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Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Chemical science (Cambridge), 2023-01, Vol.14 (2), p.226-244

2023

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Machine Learning in Computer-Aided Synthesis Planning

Accounts of chemical research, 2018-05, Vol.51 (5), p.1281-1289

2018

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Machine learning modeling of family wide enzyme-substrate specificity screens

PLoS computational biology, 2022-02, Vol.18 (2), p.e1009853-e1009853

2022

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Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction

Journal of chemical information and modeling, 2017-08, Vol.57 (8), p.1757-1772

2017

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Machine Learning‐Guided Computational Screening of New Candidate Reactions with High Bioorthogonal Click Potential

Chemistry : a European journal, 2023-05, Vol.29 (28), p.e202300387-n/a

2023

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SCScore: Synthetic Complexity Learned from a Reaction Corpus

Journal of chemical information and modeling, 2018-02, Vol.58 (2), p.252-261

2018

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

Journal of chemical information and modeling, 2019-06, Vol.59 (6), p.2529-2537

2019

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

Science (American Association for the Advancement of Science), 2019-08, Vol.365 (6453)

2019

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Autonomous platforms for data-driven organic synthesis

Nature communications, 2022-02, Vol.13 (1), p.1075-1075, Article 1075

2022

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Merging enzymatic and synthetic chemistry with computational synthesis planning

Nature communications, 2022-12, Vol.13 (1), p.7747-7747, Article 7747

2022

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Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP

Nature communications, 2022-06, Vol.13 (1), p.3342-3342, Article 3342

2022

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Automated microfluidic platform for systematic studies of colloidal perovskite nanocrystals: towards continuous nano-manufacturing

Lab on a chip, 2017-01, Vol.17 (23), p.4040-4047

2017

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Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning

Chemical science (Cambridge), 2020-09, Vol.11 (4), p.1959-1972

2020

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Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

ACS central science, 2021-08, Vol.7 (8), p.1356-1367

2021

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Computer-Assisted Retrosynthesis Based on Molecular Similarity

ACS central science, 2017-12, Vol.3 (12), p.1237-1245

2017

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Prediction of Organic Reaction Outcomes Using Machine Learning

ACS central science, 2017-05, Vol.3 (5), p.434-443

2017

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Using Machine Learning To Predict Suitable Conditions for Organic Reactions

ACS central science, 2018-11, Vol.4 (11), p.1465-1476

2018

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Reaction profiles for quantum chemistry-computed [3 + 2] cycloaddition reactions

Scientific data, 2023-02, Vol.10 (1), p.66-66, Article 66

2023

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Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor

Organic process research & development, 2018-04, Vol.22 (4), p.542-550

2018

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The Synthesizability of Molecules Proposed by Generative Models

Autonomous Discovery in the Chemical Sciences Part I: Progress

A graph-convolutional neural network model for the prediction of chemical reactivity

Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability, and explainability

Autonomous Discovery in the Chemical Sciences Part II: Outlook

Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Machine Learning in Computer-Aided Synthesis Planning

Machine learning modeling of family wide enzyme-substrate specificity screens

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction

Machine Learning‐Guided Computational Screening of New Candidate Reactions with High Bioorthogonal Click Potential

SCScore: Synthetic Complexity Learned from a Reaction Corpus

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

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

Autonomous platforms for data-driven organic synthesis

Merging enzymatic and synthetic chemistry with computational synthesis planning

Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP

Automated microfluidic platform for systematic studies of colloidal perovskite nanocrystals: towards continuous nano-manufacturing

Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery

Computer-Assisted Retrosynthesis Based on Molecular Similarity

Prediction of Organic Reaction Outcomes Using Machine Learning

Using Machine Learning To Predict Suitable Conditions for Organic Reactions

Reaction profiles for quantum chemistry-computed [3 + 2] cycloaddition reactions

Photoredox Iridium–Nickel Dual-Catalyzed Decarboxylative Arylation Cross-Coupling: From Batch to Continuous Flow via Self-Optimizing Segmented Flow Reactor

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