A new kernel has been developed for vectors derived from a coding scheme of the tri-peptide composition for protein sequences. This kernel defines the sequence similarity through a mapping that transforms a tri-peptide coding vector into a new vector based on a matrix formed by the high BLOSUM scores associated with pairs of tri-peptides. In conjunction with the use of support vector machines, the effectiveness of the new kernel is evaluated against the conventional coding schemes of k-peptide (k ≤ 3) for the prediction of subcellular localizations of proteins in Gram-negative bacteria. It is demonstrated that the new method outperforms all the other methods in a 5-fold cross-validation. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Lei, Z., & Dai, Y. (2005). A new kernel based on high-scored pairs of tri-peptides and its application in prediction of protein subcellular localization. In Lecture Notes in Computer Science (Vol. 3515, pp. 903–910). Springer Verlag. https://doi.org/10.1007/11428848_115
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