Abstract
We propose a sequence-based method to infer protein-protein interaction sites in protein hetero-complexes. The autocorrelation descriptor is used to code the numerical vectors of continuous amino acids segments. The support vector machine model combined with autocorrelation descriptor yields the best performance with a high F1 score of 46.80%, which demonstrates the effectiveness of the proposed method.
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Ren, XM., Xia, JF. (2010). Prediction of Protein-Protein Interaction Sites by Using Autocorrelation Descriptor and Support Vector Machine. In: Huang, DS., Zhang, X., Reyes GarcÃa, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_10
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DOI: https://doi.org/10.1007/978-3-642-14932-0_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14931-3
Online ISBN: 978-3-642-14932-0
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