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RESEARCH PAPER · Angewandte Chemie · 2018

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

Wiktor Beker, Ewa P. Gajewska, Tomasz Badowski, Bartosz A. Grzybowski

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22 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Prediction of Major Regio‐, Site‐, and Diastereoisomers in Diels–Alder Reactions by Using Machine‐Learning: The Importance of Physically Meaningful DescriptorsOriginalComputer-Assisted Planning of Hydroxychloroquine’s Syntheses Commencing from Inexpensive Substrates and Bypassing Patented Routes.3Computer-Assisted Planning of Hydroxychloroquine’s Syntheses Commencing from Inexpensive Substrates and Bypassing Patented Routes.2Predicting Regioselectivity in Radical C−H Functionalization of Heterocycles through Machine Learning130Predicting Regioselectivity in Radical C−H Functionalization of Heterocycles through Machine Learning24Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions42Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions15Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning78Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning6National Institutes of Health (NIH) Workshop on Reaction Informatics7Is Organic Chemistry Really Growing Exponentially?24Is Organic Chemistry Really Growing Exponentially?6Study of the Relationship between Synthesis Descriptors and the Type of Zeolite Phase Formed in ZSM‐43 Synthesis by Using Machine Learning6From Theory to Experiment: Transformer-based Generation Enables Rapid Discovery of Novel Reactions0Regioselectivity Switch Towards the Development of Innovative Diels‐Alder Cycloaddition and Productive Applications in Organic Synthesis8Machine Learning for Chemical Reactivity: The Importance of Failed Experiments217Maschinelles Lernen zur Vorhersage chemischer Reaktivität: Die Bedeutung “gescheiterter” Experimente8Reaxtica: A knowledge-guided machine learning platform for fast and accurate reaction selectivity and yield prediction0Reaxtica: A knowledge-guided machine learning platform for fast and accurate reaction selectivity and yield prediction1Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols39Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols1Extraction Yield Prediction for the Large-Scale Recovery of Botanicals1Stufenweises diversitätsbeschränktes maschinelles Lernen für die Optimierung hochdimensionaler Reaktionsbedingungen0

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  1. Computer-Assisted Planning of Hydroxychloroquine’s Syntheses Commencing from Inexpensive Substrates and Bypassing Patented Routes.

    ChemRxiv · 2020-03-25

    Sara Szymkuć, Ewa P. Gajewska, Karol Molga, Agnieszka Wołos, Rafał Roszak, Wiktor Beker, Martyna Moskal, Piotr Dittwald, Bartosz A. Grzybowski

    Read original paper ↗ ·

  2. Computer-Assisted Planning of Hydroxychloroquine’s Syntheses Commencing from Inexpensive Substrates and Bypassing Patented Routes.

    ChemRxiv · 2020-03-25

    Sara Szymkuć, Ewa P. Gajewska, Karol Molga, Agnieszka Wołos, Rafał Roszak, Wiktor Beker, Martyna Moskal, Piotr Dittwald, Bartosz A. Grzybowski

    Read original paper ↗ ·

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

    Angewandte Chemie International Edition · 2020-05-02

    Xin Li, Shuo‐Qing Zhang, Li‐Cheng Xu, Xin Hong

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

    Angewandte Chemie · 2020-05-02

    Xin Li, Shuo‐Qing Zhang, Li‐Cheng Xu, Xin Hong

    Read original paper ↗ ·

  5. Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions

    Angewandte Chemie International Edition · 2021-04-19

    Martyna Moskal, Wiktor Beker, Sara Szymkuć, Bartosz A. Grzybowski

    Read original paper ↗ ·

  6. Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions

    Angewandte Chemie · 2021-04-20

    Martyna Moskal, Wiktor Beker, Sara Szymkuć, Bartosz A. Grzybowski

    Read original paper ↗ ·

  7. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning

    Angewandte Chemie International Edition · 2021-08-09

    Li‐Cheng Xu, Shuo‐Qing Zhang, Xin Li, Miao‐Jiong Tang, Pei‐Pei Xie, Xin Hong

    Read original paper ↗ ·

  8. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning

    Angewandte Chemie · 2021-08-09

    Li‐Cheng Xu, Shuo‐Qing Zhang, Xin Li, Miao‐Jiong Tang, Pei‐Pei Xie, Xin Hong

    Read original paper ↗ ·

  9. National Institutes of Health (NIH) Workshop on Reaction Informatics

    ChemRxiv · 2021-08-19

    Wendy A. Warr

    Read original paper ↗ ·

  10. Is Organic Chemistry Really Growing Exponentially?

    Angewandte Chemie International Edition · 2021-09-24

    Sara Szymkuć, Tomasz Badowski, Bartosz A. Grzybowski

    Read original paper ↗ ·

  11. Is Organic Chemistry Really Growing Exponentially?

    Angewandte Chemie · 2021-09-24

    Sara Szymkuć, Tomasz Badowski, Bartosz A. Grzybowski

    Read original paper ↗ ·

  12. Study of the Relationship between Synthesis Descriptors and the Type of Zeolite Phase Formed in ZSM‐43 Synthesis by Using Machine Learning

    ChemistrySelect · 2021-10-18

    Ganesan Raman

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  13. From Theory to Experiment: Transformer-based Generation Enables Rapid Discovery of Novel Reactions

    Research Square · 2021-12-14

    Xinqiao Wang, Chuansheng Yao, Yun Zhang, Jiahui Yu, Haoran Qiao, Chengyun Zhang, Yejian Wu, Renren Bai, Hongliang Duan

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  14. Regioselectivity Switch Towards the Development of Innovative Diels‐Alder Cycloaddition and Productive Applications in Organic Synthesis

    Asian Journal of Organic Chemistry · 2022-02-07

    Amar Nath Singh Chauhan, Ghanshyam Mali, Rohan D. Erande

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  15. Machine Learning for Chemical Reactivity: The Importance of Failed Experiments

    Angewandte Chemie International Edition · 2022-05-05

    Felix Strieth‐Kalthoff, Frederik Sandfort, Marius Kühnemund, Felix R. Schäfer, Herbert Kuchen, Frank Glorius

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  16. Maschinelles Lernen zur Vorhersage chemischer Reaktivität: Die Bedeutung “gescheiterter” Experimente

    Angewandte Chemie · 2022-05-05

    Felix Strieth‐Kalthoff, Frederik Sandfort, Marius Kühnemund, Felix R. Schäfer, Herbert Kuchen, Frank Glorius

    Read original paper ↗ ·

  17. Reaxtica: A knowledge-guided machine learning platform for fast and accurate reaction selectivity and yield prediction

    ChemRxiv · 2022-08-21

    Kangjie Lin, Junren Li, Haoyu Lin, Jianfeng Pei, Luhua Lai

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  18. Reaxtica: A knowledge-guided machine learning platform for fast and accurate reaction selectivity and yield prediction

    ChemRxiv · 2022-08-30

    Kangjie Lin, Junren Li, Haoyu Lin, Jianfeng Pei, Luhua Lai

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  19. Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols

    Angewandte Chemie International Edition · 2023-01-16

    Naoki Noto, Akira Yada, Takeshi Yanai, Susumu Saito

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  20. Machine‐Learning Classification for the Prediction of Catalytic Activity of Organic Photosensitizers in the Nickel(II)‐Salt‐Induced Synthesis of Phenols

    Angewandte Chemie · 2023-01-16

    Naoki Noto, Akira Yada, Takeshi Yanai, Susumu Saito

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  21. Extraction Yield Prediction for the Large-Scale Recovery of Botanicals

    ChemRxiv · 2023-08-29

    Hart Plommer, Isaiah O. Betinol, Tom Dupree, Markus Roggen, Jolene P. Reid

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  22. Stufenweises diversitätsbeschränktes maschinelles Lernen für die Optimierung hochdimensionaler Reaktionsbedingungen

    Angewandte Chemie · 2026-02-15

    Shu‐Wen Li, Shan Chen, João C. A. Oliveira, Shimin Zhang, Lutz Ackermann, Xin Hong

    Read original paper ↗ ·
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