Abstract
Hepatitis C virus (HCV) infection is a major cause of liver disease and a dangerous threat to public health. Hence, the problem of interactions between HCV and human proteins has received much attention. In the present study, we propose a support vector machine (SVM) model for predicting the binding residues in HCV protein complexes. The SVM model achieved an average sensitivity of 76.06% and specificity of 75.94% for 18 non-redundant HCV protein complexes. This approach can efficiently search potential protein-binding sites in proteins and a wide range of protein-protein interaction sites.
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Yoo, T., Lee, J., Han, K. (2008). Prediction of Binding Sites in HCV Protein Complexes Using a Support Vector Machine. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_18
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DOI: https://doi.org/10.1007/978-3-540-87442-3_18
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