Predicting and analyzing organic reaction pathways by combining machine learning and reaction network approaches

  • Tomonori Ida
    Division of Material Chemistry, Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan
  • Honoka Kojima
    Division of Material Chemistry, Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan
  • Yuta Hori
    Center for Computational Sciences, University of Tsukuba, Tsukuba 305-8577, Japan

書誌事項

公開日
2023
資源種別
journal article
権利情報
  • http://creativecommons.org/licenses/by-nc/3.0/
DOI
  • 10.1039/d3cc03890d
公開者
Royal Society of Chemistry (RSC)

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説明

<jats:p>By training 50 fundamental organic reactions, the learning model predicted the products and pathways of 35 test reactions. The model identified the key fragment structures of the reaction intermediates.</jats:p>

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