{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236990","sets":["6504:11678:11684"]},"path":["11684"],"owner":"44499","recid":"236990","title":["タンパク質分子のトポロジーと立体構造に基づくGCNによるEC番号の推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"0d7fe9c2-c8ca-4c38-a16d-8c54ffdb3651"},"_deposit":{"id":"236990","pid":{"type":"depid","value":"236990","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"タンパク質分子のトポロジーと立体構造に基づくGCNによるEC番号の推定","author_link":["647998","647999","648000","647997"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"タンパク質分子のトポロジーと立体構造に基づくGCNによるEC番号の推定"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータと人間社会","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京薬科大"},{"subitem_text_value":"東京薬科大"},{"subitem_text_value":"東京薬科大"},{"subitem_text_value":"東京薬科大"}]},"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/236990/files/IPSJ-Z86-4ZK-04.pdf","label":"IPSJ-Z86-4ZK-04.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-04"}],"format":"application/pdf","filename":"IPSJ-Z86-4ZK-04.pdf","filesize":[{"value":"326.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"e63514e8-d9df-498c-9a4e-58a5cc5b5c84","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"竹内, 啓"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"青柳, 詠美"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"丸山, 直道"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小島, 正樹"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"当研究室では、タンパク質分子の位相幾何学的特徴に基づく立体構造をグラフとして表現するVOLTESプログラムを開発し、論理的構造設計や分子進化とトポロジーとの相関解析に適用してきた。本研究ではVOLTESの機械学習への応用を目指し、AIの特徴量としての有用性を確認するため、独自の手法でグラフ畳み込みニューラルネットワーク(GCN)を構築して、酵素分子の立体構造とトポロジー情報からEC番号の推定を行った。特に、VOLTESデータ特有の分子情報に着目してカテゴリー化およびグループ化を行い、これらを新たに加味した特徴量を考案して評価を実施したところ、高い有効性を確認できた。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"766","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"765","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236990,"updated":"2025-01-19T09:02:30.816626+00:00","links":{},"created":"2025-01-19T01:39:21.732381+00:00"}