Predicting and analyzing organic reaction pathways by combining machine learning and reaction network approaches
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- Tomonori Ida
- Division of Material Chemistry, Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan
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- Honoka Kojima
- Division of Material Chemistry, Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan
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- 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
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- http://creativecommons.org/licenses/by-nc/3.0/
- DOI
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- 10.1039/d3cc03890d
- 公開者
- Royal Society of Chemistry (RSC)
この論文をさがす
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>
収録刊行物
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- Chemical Communications
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Chemical Communications 59 (83), 12439-12442, 2023
Royal Society of Chemistry (RSC)
