{"created":"2021-03-01T06:18:23.034616+00:00","id":1796,"links":{},"metadata":{"_buckets":{"deposit":"a9329dba-3e68-4812-927a-36f1e978a208"},"_deposit":{"id":"1796","owners":[],"pid":{"revision_id":0,"type":"depid","value":"1796"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00001796","sets":["6:260:261","9:233:234"]},"item_7_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2007-02-02","bibliographicIssueDateType":"Issued"},"bibliographic_titles":[{}]}]},"item_7_date_granted_25":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2007-03"}]},"item_7_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"本論文では複数の漸化式・微分方程式モデルによる遺伝子制御ネットワークの推定結果をAdaBoostにより統合する方法を提案する．発現量時系列データから遺伝子制御ネットワークを推定するためにS-systemや線形モデルなどの様々な漸化式・微分方程式モデルが提案されている．現在は特定のモデルがターゲットとするネットワークの推定に適していると仮定して推定が行われている．しかしながら，複数のモデルが提案されている状況から分かるように，対象とする時系列データに対してどのモデルが推定に適しているか不明であるという問題がある．この問題に対して複数の漸化式・微分方程式モデルによる統合的な推定方法は有効であると考えられる．本論文ではAdaBoostを用いた複数の推定手法（モデル）の統合を提案し，さらに推定実験を行い提案手法の有効性を示す．","subitem_description_type":"Abstract"},{"subitem_description":"In order to estimate Gene Regulatory Networks (GRNs) from gene expression time series data, various recurrence or differential equation based models have been proposed, such as S-system, Linear model etc. Generally, it is assumed that a specific recurrence or differential equation model is sufficient to estimate the network from the expression profile. However, with so many different models available, it is not easy to recognize the model that will be most suitable for a particular network inference problem. To deal with the problem, integrative estimation with multiple recurrence or differential equation based models seems promising. In this paper, we propose the integration of multiple estimation methods by means of AdaBoost. Empirical studies show the effectiveness of our proposal.","subitem_description_type":"Abstract"}]},"item_7_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"5587","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Nabatame, Shinya"}]}]},"item_7_select_21":{"attribute_name":"学位","attribute_value_mlt":[{"subitem_select_item":"master"}]},"item_7_subject_13":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_7_text_24":{"attribute_name":"研究科・専攻","attribute_value_mlt":[{"subitem_text_value":"工学系研究科電子工学専攻"}]},"item_7_text_27":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_text_value":"修第号"}]},"item_7_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学大学院工学系研究科 電子工学専攻"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"生田目, 慎也"}],"nameIdentifiers":[{"nameIdentifier":"5586","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-05-31"}],"displaytype":"detail","filename":"namatame.pdf","filesize":[{"value":"1.0 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"namatame.pdf","url":"https://repository.dl.itc.u-tokyo.ac.jp/record/1796/files/namatame.pdf"},"version_id":"5e6e7c90-2983-4b3b-a63c-be5aef178f62"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"バイオインフォマティクス","subitem_subject_scheme":"Other"},{"subitem_subject":"遺伝子制御ネットワーク","subitem_subject_scheme":"Other"}]},"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":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"AdaBoostを用いた遺伝子制御ネットワークの統合的推定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"AdaBoostを用いた遺伝子制御ネットワークの統合的推定"}]},"item_type_id":"7","owner":"1","path":["234","261"],"pubdate":{"attribute_name":"公開日","attribute_value":"2011-08-08"},"publish_date":"2011-08-08","publish_status":"0","recid":"1796","relation_version_is_last":true,"title":["AdaBoostを用いた遺伝子制御ネットワークの統合的推定"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T03:43:13.654062+00:00"}