Comparative Study of Score Functions for Edge Orientation in Genetic Network Estimation

• Item type: SIG Technical Reports(1)
• 公開日: 2009-12-10
• タイトル: Comparative Study of Score Functions for Edge Orientation in Genetic Network Estimation
• タイトル / 言語: en
• タイトル: Comparative Study of Score Functions for Edge Orientation in Genetic Network Estimation
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Graduate School of the University of the Ryukyus, Information Engineering
• 著者所属: University of the Ryukyus, Information Engineering
• 著者所属: University of the Ryukyus, Information Engineering
• 著者所属(英): en
• 著者所属(英): Graduate School of the University of the Ryukyus, Information Engineering
• 著者所属(英): en
• 著者所属(英): University of the Ryukyus, Information Engineering
• 著者所属(英): en
• 著者所属(英): University of the Ryukyus, Information Engineering
• 著者名: Hitoshi, Afuso; Takeo, Okazaki; Morikazu, Nakamura
• 著者名(英): Hitoshi, Afuso; Takeo, Okazaki; Morikazu, Nakamura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In this paper, we compare the score functions for edge orientation problem in estimation of genetic network from DNA microarray data. We focused four score functions, Standard Bayesian Metric( SBM), Bayesian Dirichlet Metric(BDM), K2 Metric and PageRank Orientation Metric(PROM). To compare and evaluate the performance of each score function in various situations, we utilized the generation method of artificial genetic networks and DNA microarray data and used those artificial data. To generate the networks that have certain network property, such as scale-free property, we used certain network generation models such as Barabasi-Albert Model. In the experiments, the number of edges such that orientated incorrectly was used to evaluate the performance of the score function.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In this paper, we compare the score functions for edge orientation problem in estimation of genetic network from DNA microarray data. We focused four score functions, Standard Bayesian Metric( SBM), Bayesian Dirichlet Metric(BDM), K2 Metric and PageRank Orientation Metric(PROM). To compare and evaluate the performance of each score function in various situations, we utilized the generation method of artificial genetic networks and DNA microarray data and used those artificial data. To generate the networks that have certain network property, such as scale-free property, we used certain network generation models such as Barabasi-Albert Model. In the experiments, the number of edges such that orientated incorrectly was used to evaluate the performance of the score function.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN10505667
• 書誌情報: 研究報告数理モデル化と問題解決（MPS）; 巻 2009-MPS-76, 号 20, p. 1-7, 発行日 2009-12-10
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会