Bacterial lipoproteins have many important functions owing to their essential nature and roles in pathogenesis and represent a class of possible vaccine candidates. The prediction of bacterial lipoproteins from sequence is thus an important task for computational vaccinology. A Support Vector Machines (SVM) based module for predicting bacterial lipoproteins, LIPOPREDICT, has been developed. The best performing sequence model were generated using selected dipeptide composition, which gave 97% accuracy of prediction. The results obtained were compared very well with those of previously developed methods.
CITATION STYLE
Kumari, S. R., Kadam, K., Badwaik, R., & Jayaraman, V. K. (2012). LIPOPREDICT: Bacterial lipoprotein prediction server. Bioinformation, 8(8), 394–398. https://doi.org/10.6026/97320630008394
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