{"created":"2023-07-27T06:52:17.777039+00:00","id":46119,"links":{},"metadata":{"_buckets":{"deposit":"c995b13a-2b42-48c6-9e45-29aa7fade160"},"_deposit":{"created_by":18,"id":"46119","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"46119"},"status":"published"},"_oai":{"id":"oai:kanazawa-u.repo.nii.ac.jp:00046119","sets":["2812:2813:2816"]},"author_link":["79985","2669"],"item_9_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-06-15","bibliographicIssueDateType":"Issued"},"bibliographicPageStart":"4p.","bibliographicVolumeNumber":"2014-04-01 - 2018-03-31","bibliographic_titles":[{"bibliographic_title":"平成29(2017)年度 科学研究費補助金 基盤研究(C) 研究成果報告書"},{"bibliographic_title":"2017 Fiscal Year Final Research Report","bibliographic_titleLang":"en"}]}]},"item_9_creator_33":{"attribute_name":"著者別表示","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{}],"nameIdentifiers":[{},{}]}]},"item_9_description_21":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"塩基配列や、それから転写・翻訳されてできるアミノ酸配列を解析する際、分子生物学の知識に大きく依存した従来的な方法では、ある程度予想可能な事実しか発見できないという限界があった。本研究ではディープラーニングを含む各種の機械学習手法を用いることで、大規模な配列データから道の階層的な特徴を抽出することが可能であることを明らかにした。","subitem_description_type":"Abstract"},{"subitem_description":"In the field of biological sequence analysis including DNA and amino acid sequence analysis, traditional methods are highly dependent on the knowledge specific to molecular biology, so their ability is limited to the discovery of features easily predicted from domain-specific knowledge. In this study, it is shown that by using various machine learning algorithms including deep learning, it is possible to extract novel and hierarchical features from large sequence data.","subitem_description_type":"Abstract"}]},"item_9_description_22":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"研究課題/領域番号:26330328, 研究期間(年度):2014-04-01 - 2018-03-31","subitem_description_type":"Other"},{"subitem_description":"出典：研究課題「ディープラーニングを用いた大規模配列データからの階層的特徴抽出」課題番号26330328\n（KAKEN：科学研究費助成事業データベース（国立情報学研究所）） \n（https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-26330328/26330328seika/）を加工して作成","subitem_description_type":"Other"}]},"item_9_description_5":{"attribute_name":"提供者所属","attribute_value_mlt":[{"subitem_description":"金沢大学理工研究域生命理工学系","subitem_description_type":"Other"}]},"item_9_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.24517/00052453","subitem_identifier_reg_type":"JaLC"}]},"item_9_relation_28":{"attribute_name":"関連URI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/search/?qm=10215783"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/search/?qm=10215783","subitem_relation_type_select":"URI"}},{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-26330328/"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-26330328/","subitem_relation_type_select":"URI"}},{"subitem_relation_name":[{"subitem_relation_name_text":"https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-26330328/26330328seika/"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-26330328/26330328seika/","subitem_relation_type_select":"URI"}}]},"item_9_version_type_25":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-04-25"}],"displaytype":"detail","filename":"TE-PR-SATO-K-kaken 2018-4p.pdf","filesize":[{"value":"180.7 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"TE-PR-SATO-K-kaken 2018-4p.pdf","url":"https://kanazawa-u.repo.nii.ac.jp/record/46119/files/TE-PR-SATO-K-kaken 2018-4p.pdf"},"version_id":"885f9df2-4d06-43f4-98fe-7aa89cbe6e29"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"research report","resourceuri":"http://purl.org/coar/resource_type/c_18ws"}]},"item_title":"ディープラーニングを用いた大規模配列データからの階層的特徴抽出","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ディープラーニングを用いた大規模配列データからの階層的特徴抽出"},{"subitem_title":"Hierarchical Feature Extraction from Large Sequence Data by Deep Learning","subitem_title_language":"en"}]},"item_type_id":"9","owner":"18","path":["2816"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-04-25"},"publish_date":"2019-04-25","publish_status":"0","recid":"46119","relation_version_is_last":true,"title":["ディープラーニングを用いた大規模配列データからの階層的特徴抽出"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2023-07-27T12:56:21.531101+00:00"}