Journal of Applied Sciences
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MENG Wei, WANG Fei-fei, PENG Xin-jun, SHEN Chen-yi, WANG Yi-fei
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Abstract: Identification of protein-protein interaction sites is essential for the mutant design and prediction of protein-protein networks. This paper proposes a method for predicting protein-protein interaction sites by combining support vector machine (SVM) and the sequence profiles, the accessible surface area (ASA) and the evolution rate of a residue. The dataset is trained and tested using 10-fold cross-validation. Accuracy of the proposed method is 72.91%, 5.71% higher than that of the method only using the sequence profiles and the evolution rate of a residue.
Key words: protein-protein interaction sites, support vector machine (SVM), sequence profiles, accessible surface area, evolution rate
MENG Wei;WANG Fei-fei;PENG Xin-jun;SHEN Chen-yi;WANG Yi-fei. Prediction of Protein-Protein Interaction Sites Using Support Vector Machine[J]. Journal of Applied Sciences.
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