Conditional Random Field Approach to Prediction of Protein-protein Interactions Using Domain Information

• Item type: SIG Technical Reports(1)
• 公開日: 2011-03-03
• タイトル: Conditional Random Field Approach to Prediction of Protein-protein Interactions Using Domain Information
• タイトル / 言語: en
• タイトル: Conditional Random Field Approach to Prediction of Protein-protein Interactions Using Domain Information
• 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: Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者所属: Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者所属: Department of Biochemistry and Molecular Biology, Monash University, Australia／Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, China
• 著者所属: Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者所属(英): en
• 著者所属(英): Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者所属(英): en
• 著者所属(英): Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者所属(英): en
• 著者所属(英): Department of Biochemistry and Molecular Biology, Monash University, Australia / Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, China
• 著者所属(英): en
• 著者所属(英): Bioinformatics Center, Institute for Chemical Research, Kyoto University
• 著者名: Morihiro, Hayashida; Mayumi, Kamada; Jiangning, Song; Tatsuya, Akutsu
• 著者名(英): Morihiro, Hayashida; Mayumi, Kamada; Jiangning, Song; Tatsuya, Akutsu
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Analysis of functions and interactions of proteins and domains is important for understanding cellular systems and biological networks. Many methods for predicting protein-protein interactions have been developed. It is known that mutual information between residues at interacting sites can be higher than that at non-interacting sites. It is based on the thought that amino acid residues at interacting sites have coevolved with those at the corresponding residues in the partner proteins. Several studies have shown that such mutual information is useful for identifying contact residues in interacting proteins. We propose novel methods using conditional random fields for predicting protein-protein interactions. We focus on the mutual information between residues, and combine it with conditional random fields. In the methods, protein-protein interactions are modeled using domain-domain interactions. We perform computational experiments using protein-protein interaction datasets for several organisms, and calculate AUC (Area Under ROC Curve) score. The results suggest that our proposed methods with and without mutual information outperform EM (Expectation Maximization) method proposed by Deng et al.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Analysis of functions and interactions of proteins and domains is important for understanding cellular systems and biological networks. Many methods for predicting protein-protein interactions have been developed. It is known that mutual information between residues at interacting sites can be higher than that at non-interacting sites. It is based on the thought that amino acid residues at interacting sites have coevolved with those at the corresponding residues in the partner proteins. Several studies have shown that such mutual information is useful for identifying contact residues in interacting proteins. We propose novel methods using conditional random fields for predicting protein-protein interactions. We focus on the mutual information between residues, and combine it with conditional random fields. In the methods, protein-protein interactions are modeled using domain-domain interactions. We perform computational experiments using protein-protein interaction datasets for several organisms, and calculate AUC (Area Under ROC Curve) score. The results suggest that our proposed methods with and without mutual information outperform EM (Expectation Maximization) method proposed by Deng et al.
• 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: AA12055912
• 書誌情報: 研究報告バイオ情報学（BIO）; 巻 2011-BIO-24, 号 11, p. 1-6, 発行日 2011-03-03
• 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