CONFORMATIONAL B-CELL EPITOPES CLASSIFICATION USING MACHINE LEARNING TECHNIQUES

Vaccination is one of the most important and successful public health interventions to human lives. Computational techniques presented by bioinformatics seem to be believed by many scientists that it can contribute significantly in the vaccine design process. They can overcome the time and money limitations of the traditional used methods. One essential step in the vaccine design process is the B-cell epitope prediction. Synthetic peptides can be developed after reaching an accurate prediction degree. As most B-cell epitopes are known to be conformational (discontinuous), it’s vital to develop modules to enhance its prediction results. In this paper, a classification model for classifying conformational b-cell epitopes is proposed. This model depends on the machine learning techniques for classification and clustering. The model achieved high performance on the train data