{"created":"2025-01-19T01:16:19.669438+00:00","updated":"2025-01-19T16:06:09.056733+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215562","sets":["6504:10735:10811"]},"path":["10811"],"owner":"44499","recid":"215562","title":["適用領域を考慮した薬剤標的親和性予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"d244b7f0-f9c6-4154-b0a4-1b6ff28fd7b6"},"_deposit":{"id":"215562","pid":{"type":"depid","value":"215562","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"適用領域を考慮した薬剤標的親和性予測","author_link":["555069","555070"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"適用領域を考慮した薬剤標的親和性予測"}]},"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":"2021-03-04","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":"東工大"},{"subitem_text_value":"東工大"}]},"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/215562/files/IPSJ-Z83-4ZC-05.pdf","label":"IPSJ-Z83-4ZC-05.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-29"}],"format":"application/pdf","filename":"IPSJ-Z83-4ZC-05.pdf","filesize":[{"value":"537.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"19aaeb46-36b6-4033-8ebd-624fcb5fc8fd","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"杉田, 駿也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大上, 雅史"}],"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":"計算機による創薬支援のため、化合物と標的分子の親和性を網羅的に予測する薬剤標的親和性予測が行われている。化合物-標的分子間の相互作用の既知情報、化合物の構造情報、標的分子(タンパク質)の配列情報などを用いた教師あり学習に基づく予測手法が、これまでに数多く報告されてきた。しかし、予測の適用領域を考慮した予測モデル構築は現在まで行われておらず、入力された化合物-標的ペアの特徴量に対してモデルが信頼性を持って予測できるかについては研究されてこなかった。本稿では教師あり学習における適用領域を考慮した、薬剤標的親和性予測手法を提案し、実際に親和性の回帰予測精度を改善することを示した。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"476","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"475","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":215562,"links":{}}