{"created":"2025-01-19T01:36:42.079143+00:00","updated":"2025-01-19T09:41:39.040295+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00234845","sets":["1164:5352:11553:11625"]},"path":["11625"],"owner":"44499","recid":"234845","title":["コンセンサス予測を用いた化合物逆合成解析"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-13"},"_buckets":{"deposit":"d851434e-d2d9-48ff-b6b7-210413d14efa"},"_deposit":{"id":"234845","pid":{"type":"depid","value":"234845","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"コンセンサス予測を用いた化合物逆合成解析","author_link":["640676","640677"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"コンセンサス予測を用いた化合物逆合成解析"},{"subitem_title":"Retrosynthesis Analysis with Consensus Prediction","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"バイオ情報学1","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-06-13","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学情報理工学院情報工学系知能情報コース"},{"subitem_text_value":"東京工業大学情報理工学院情報工学系知能情報コース"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science, School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/234845/files/IPSJ-BIO24078018.pdf","label":"IPSJ-BIO24078018.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-13"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO24078018.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"18f98d09-1e5d-48a6-a7d4-ac593d46723a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"篠原, 旭"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石田, 貴士"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12055912","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8590","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"目的化合物を簡単かつ安価に手に入る化合物になるまで化学的に合理的な切断を繰り返すことにより合成経路を設計する手法である多段階逆合成解析は，合成経路を設計するために非常に有用な解析である．そこで各ステップの予測精度を目的に，1 ステップの逆合成反応のみを考えたシングルステップ逆合成解析に関する研究が数多く行われている．テンプレートベースの手法は，テンプレートを参照した予測に対しては高い性能を発揮するが，汎化性能に欠ける，テンプレートフリー手法では，テンプレートベース手法における欠点は解決されるが，予測精度が少し下がってしまう傾向にある．どちらの手法も一長一短であり，折衷案となるモデルを開発することは難しい．そこで本研究では，シングルステップ逆合成解析の精度の向上のためにコンセンサス予測を利用する手法を提案する．テンプレートベース，テンプレートフリーモデルから各 2 つずつ，計 4 つのモデルから得られた予測結果のうち，一致する化合物の順位に対し，平均や調和平均を取る，または先頭に移動させると言った処理を行ったのちに，再順位付けする．この処理によって得られた予測精度を元の 4 つのモデルと比較すると，精度が大きく向上することが確認できた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Multi-step retrosynthetic analysis, a method of designing synthesis routes by repeatedly applying chemically rational disconnections to the target compound until it becomes a simple and inexpensive compound, is an extremely useful analysis for designing synthesis routes. Therefore, numerous studies have been conducted on single-step retrosynthetic analysis, which considers only one-step retrosynthetic reactions, with the aim of improving the prediction accuracy of each step. Template-based methods exhibit high performance for predictions based on template referencing but lack generalization ability. Template-free methods solve the shortcomings of template-based methods, but they tend to have slightly lower prediction accuracy. Both methods have their pros and cons, and it is difficult to develop a model that serves as a compromise. Therefore, in this study, we propose a method that utilizes consensus prediction to improve the accuracy of single-step retrosynthetic analysis. Among the prediction results obtained from a total of four models, two each from template-based and template-free models, the ranks of the matching compounds are processed by taking the mean or harmonic mean, or by moving them to the top, and then re-ranking is performed. By comparing the prediction accuracy obtained through this process with the original four models, it was confirmed that the accuracy greatly improved.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"18","bibliographicVolumeNumber":"2024-BIO-78"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":234845,"links":{}}