並列タイトル等Novel Methods for Chemical Compound Inference Based on Machine Learning and Mixed Integer Linear Programming
一般注記機関リポジトリ記載の権利情報: Chapter 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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