Predicting Protein-RNA Residue-base Contacts Using Two-dimensional Conditional Random Field

• Item type: SIG Technical Reports(1)
• 公開日: 2012-08-02
• タイトル: Predicting Protein-RNA Residue-base Contacts Using Two-dimensional Conditional Random Field
• タイトル / 言語: en
• タイトル: Predicting Protein-RNA Residue-base Contacts Using Two-dimensional Conditional Random Field
• 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／Presently with Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences
• 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 / Presently with Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences
• 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: It is important to understand interactions between proteins and RNAs for uncovering networks and functions of molecules in cellular systems. Many researchers have studied for analyzing and investigating interactions between protein residues and RNA bases. For interactions between protein residues, it is supported that residues at interacting sites have co-evolved with the corresponding residues in the partner protein to keep the interactions between the proteins. In our previous work, on the basis of this idea, we calculated mutual information (MI) between residues from multiple sequence alignments of homologous proteins for identifying interacting pairs of residues in interacting proteins, and combined it with the discriminative random field (DRF), which is useful to extract some characteristic regions from an image in the field of image processing, and is a special type of conditional random fields (CRFs). In a similar way, in this technical report, we make use of mutual information for predicting interactions between protein residues and RNA bases. Furthermore, we introduce labels of amino acids and bases as features of a simple two-dimensional CRF instead of DRF. To evaluate our method, we perform computational experiments for several interactions between Pfam domains and Rfam entries. The results suggest that the CRF model with MI and labels is more useful than the CRF model with only MI.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: It is important to understand interactions between proteins and RNAs for uncovering networks and functions of molecules in cellular systems. Many researchers have studied for analyzing and investigating interactions between protein residues and RNA bases. For interactions between protein residues, it is supported that residues at interacting sites have co-evolved with the corresponding residues in the partner protein to keep the interactions between the proteins. In our previous work, on the basis of this idea, we calculated mutual information (MI) between residues from multiple sequence alignments of homologous proteins for identifying interacting pairs of residues in interacting proteins, and combined it with the discriminative random field (DRF), which is useful to extract some characteristic regions from an image in the field of image processing, and is a special type of conditional random fields (CRFs). In a similar way, in this technical report, we make use of mutual information for predicting interactions between protein residues and RNA bases. Furthermore, we introduce labels of amino acids and bases as features of a simple two-dimensional CRF instead of DRF. To evaluate our method, we perform computational experiments for several interactions between Pfam domains and Rfam entries. The results suggest that the CRF model with MI and labels is more useful than the CRF model with only MI.
• 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 2012-BIO-30, 号 4, p. 1-6, 発行日 2012-08-02
• 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