SVR-PAIRWISE method to predict MHC-II binding peptides
by Juan Liu, Lian Wang, Shanfeng Zhu
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 6, No. 1, 2010

Abstract: Peptides binding to MHC molecules is of great importance in the process of triggering and initiating immune responses. There are two main kinds of MHC molecules, MHC class I and class II, and the prediction of MHC-II binding peptides is much more difficult due to their variable lengths, which makes it difficult to construct a preferable prediction model by using most of the existing methods. This paper presents a method, called as SVR-PAIRWISE, to combine Support Vector Regression (SVR) and pairwise alignment, to quantitatively predict the MHC-II binding peptides. The comparison results with some popular methods show its satisfying performances.

Online publication date: Wed, 27-Jan-2010

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