Download the SVM STANDALONE (wxPython) for MAC
The dipeptide composition of the positive and negative dataset sequences was calculated and given as input to the SVMlight software to generate prediction models.
To increase the robustness of prediction, we used the hybrid model by integrating motif based and SVM based methods. If the user's query peptide has the any one of the motifs as those from our datasets, we assign peptide type to it based on motif that it contains. SVM model of prediction is used in case no motif is found.