Welcome to the Home Page of PVP-SVM


PVP-SVM is web based prediction server for bacteriophage virion proteins. SVM-based prediction model was developed using the optimal feature set selected by random forest. The optimal feature set includes, amino acid composition, atomic composition, dipeptide composition, and physiochemical properties as an input feature. For a given peptide, PVP-SVM predicts its calss and probability values.


Enter the protein sequences in FASTA format (Example)



File:








Reference

PVP-SVM: sequence-based prediction of bacteriophage virion proteins using a support vector machine (Frontiers in Microbiology).
 [Please cite this paper if you find PVP-SVM useful in your research] 

Contact: bala@kias.re.kr