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Many proteins can interact with other proteins to perform specific functions. Predicting those interactions is important in order to analyze signaling pathways or to define the influence of a specific protein in some diseases. This work proposes the implementation of Support Vector Machines (SVM) for the prediction of protein-protein interactions using physical-chemical features taken from AA index...
In this paper, a SVM-based method is implemented for the prediction of protein-protein interactions. This model is initially trained with a set of over 69.000 pairs of protein sequences based on documented positive interactions. Then, a cross-validation method is performed for estimating the accuracy of the system, showing acceptable performances in terms of sensitivity, specificity and geometric...
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