Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information

• Item type: Trans(1)
• 公開日: 2008-03-15
• タイトル: Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information
• タイトル / 言語: en
• タイトル: Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Original Papers
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Department of Biotechnology Graduate School of Agricultural and Life Sciences The University of Tokyo
• 著者所属: Department of Biotechnology Graduate School of Agricultural and Life Sciences The University of Tokyo
• 著者所属: Department of Biotechnology Graduate School of Agricultural and Life Sciences The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
• 著者所属(英): en
• 著者所属(英): Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
• 著者名: Masanori, Kakuta; Shugo, Nakamura; Kentaro, Shimizu
• 著者名(英): Masanori, Kakuta; Shugo, Nakamura; Kentaro, Shimizu
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Protein-protein interactions play an important role in a number of biological activities. We developed two methods of predicting protein-protein interaction site residues. One method uses only sequence information and the other method uses both sequence and structural information. We used support vector machine (SVM) with a position specific scoring matrix (PSSM) as sequence information and accessible surface area (ASA) of polar and non-polar atoms as structural information. SVM is used in two stages. In the first stage an interaction residue is predicted by taking PSSMs of sequentially neighboring residues or taking PSSMs and ASAs of spatially neighboring residues as features. The second stage acts as a filter to refine the prediction results. The recall and precision of the predictor using both sequence and structural information are 73.6% and 50.5% respectively. We found that using PSSM instead of frequency of amino acid appearance was the main factor of improvement of our methods.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Protein-protein interactions play an important role in a number of biological activities. We developed two methods of predicting protein-protein interaction site residues. One method uses only sequence information and the other method uses both sequence and structural information. We used support vector machine (SVM) with a position specific scoring matrix (PSSM) as sequence information and accessible surface area (ASA) of polar and non-polar atoms as structural information. SVM is used in two stages. In the first stage, an interaction residue is predicted by taking PSSMs of sequentially neighboring residues or taking PSSMs and ASAs of spatially neighboring residues as features. The second stage acts as a filter to refine the prediction results. The recall and precision of the predictor using both sequence and structural information are 73.6% and 50.5%, respectively. We found that using PSSM instead of frequency of amino acid appearance was the main factor of improvement of our methods.
• 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: AA12177013
• 書誌情報: IPSJ Transactions on Bioinformatics （TBIO）; 巻 49, 号 SIG5(TBIO4), p. 25-35, 発行日 2008-03-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-6679
• 出版者 / 言語: ja
• 出版者: 情報処理学会