LIPOPREDICT: bacterial lipoprotein prediction server |
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Authors: | Kumari S Ramya Kadam Kiran Badwaik Ritesh Jayaraman Valadi K |
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Affiliation: | Centre for Development of Advanced Computing (C-DAC), Pune University Campus, Ganeshkind, Pune-411 007, India. |
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Abstract: | 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. |
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Keywords: | Bacterial lipoproteins Support Vector Machine (SVM) compositional features prediction server |
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