A new kernel based on high-scored pairs of tri-peptides and its application in prediction of protein subcellular localization

Authors:
Zhengdeng Lei;Yang Dai
Affiliations:
Department of Bioengineering (MC063), University of Illinois at Chicago, Chicago, IL;Department of Bioengineering (MC063), University of Illinois at Chicago, Chicago, IL
Venue:
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Year:
2005

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Abstract

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.