@techreport{oai:ipsj.ixsq.nii.ac.jp:00094396,
 author = {Yusuke, Sakuma and Mayumi, Kamada and Morihiro, Hayashida and Tatsuya, Akutsu and Yusuke, Sakuma and Mayumi, Kamada and Morihiro, Hayashida and Tatsuya, Akutsu},
 issue = {1},
 month = {Jul},
 note = {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.},
 title = {Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression},
 year = {2013}
}