2026-06-17T13:33:28Z https://ipsj.ixsq.nii.ac.jp/oai

oai:ipsj.ixsq.nii.ac.jp:00094396 2025-01-21T14:37:38Z 1164:2735:7088:7226

Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression Yusuke, Sakuma Mayumi, Kamada Morihiro, Hayashida Tatsuya, Akutsu Yusuke, Sakuma Mayumi, Kamada Morihiro, Hayashida Tatsuya, Akutsu Due to the importance of protein-protein interactions (PPIs) in living organisms, many efforts have been made to investigate and predict PPIs. Analysis of strengths of PPIs is important as well as PPIs because such strengths are involved in functionality of proteins. In this technical report, we propose several feature space mappings from protein pairs, which make use of protein domain information, and perform five-fold cross-validation for data obtained from biological experiments. The result of average root mean square error (RMSE) using support vector regression (SVR) with our proposed feature was better than that by the best existing method, APM proposed by Chen et al. Due to the importance of protein-protein interactions (PPIs) in living organisms, many efforts have been made to investigate and predict PPIs. Analysis of strengths of PPIs is important as well as PPIs because such strengths are involved in functionality of proteins. In this technical report, we propose several feature space mappings from protein pairs, which make use of protein domain information, and perform five-fold cross-validation for data obtained from biological experiments. The result of average root mean square error (RMSE) using support vector regression (SVR) with our proposed feature was better than that by the best existing method, APM proposed by Chen et al. technical report 情報処理学会 2013-07-15 application/pdf 研究報告数理モデル化と問題解決（MPS） 1 2013-MPS-94 1 4 AN10505667 https://ipsj.ixsq.nii.ac.jp/record/94396/files/IPSJ-MPS13094001.pdf eng