A new peptide encoding scheme is proposed to use with support vector machines for the direct recognition of T cell epitopes. The method enables the presentation of information on both (1) amino acid positions in peptides and (2) the similarity between amino acids through the use of sparse indicator vectors and the BLOSUM50 matrix. A procedure of feature selection is also introduced. The computational results demonstrate superior performance over previous techniques.
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