Abstract
AbstractO-glycosylation is one of the main types of the mammalian protein glycosylation, it occurs on the particular site of serine and threonine. It’s important to predict the O-glycosylation site. In this paper, we proposed a new method of combining kernel principal component analysis(KPCA) and artificial neural network(ANN) to predict the O-glycosylation site. The samples for experiment are encoded by the sparse coding with window size w=21. We first extracted the features of the original data by kernel principal component analysis, and then used artificial neural network to classify the test samples into two classes(positive and negative). The results of experiments show that the proposed method is more effective and accurate than PCA+ANN. The prediction accuracy is about 88.5%.KeywordspredictionglycosylationproteinKPCAANN
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