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Novel Methods for Chemical Compound Inference Based on Machine Learning and Mixed Integer Linear Programming / 機械学習と混合整数線形計画法に基づく新しい化合物推定手法

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24938号 / 情博第849号 / 新制||情||142(附属図書館) / 京都大学大学院情報学研究科数理工学専攻 / (主査)准教授 原口 和也, 教授 山下 信雄, 教授 阿久津 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Identiferoai:union.ndltd.org:kyoto-u.ac.jp/oai:repository.kulib.kyoto-u.ac.jp:2433/285872
Date25 September 2023
CreatorsZhu, Jianshen
Contributors朱, 見深, シュ, ケンシン
PublisherKyoto University, 京都大学
Source SetsKyoto University
LanguageEnglish
Detected LanguageEnglish
Typedoctoral thesis, Thesis or Dissertation
RightsChapter 5 is adapted from [Zhu et al., A novel method for inferring chemical compounds with prescribed topological substructures based on integer programming. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(6):3233–3245, 2021], https://doi.org/10.1109/TCBB.2021.3112598, Copyright ©︎IEEE 2021. In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Kyoto University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation. Chapter 7 is adapted from [Zhu et al., Adjustive linear regression and its application to the inverse QSAR. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS, pages 144–151. INSTICC, SciTePress, 2022], https://doi.org/10.5220/0010853700003123, with permission from the publisher. Copyright ©︎SCITEPRESS 2022. Chapters 4, 6, and 8 are adapted from https://doi.org/10.3390/a13050124, https://doi.org/10.31083/j.fbl2706188, and https://doi.org/10.48550/arXiv.2209.13527, respectively, and have been reproduced with the permission of the publisher under CC-BY license.

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