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Predicting protein functions is an important issue in the post-genomic era. This paper studies several network-based kels including local linear embedding (LLE) kel method, diffusion kel and laplacian kel to uncover the relationship between proteins functions and protein-protein interactions (PPI). The author first construct kels based on PPI networks, then apply support vector machine (SVM) techniques to classify proteins into different functional groups. The 5-fold cross validation is then applied to the selected 359 GO terms to compare the performance of different kels and guilt-by-association methods including neighbor counting methods and Chi-square methods.Finally, the authors conduct predictions of functions of some unknown genes and verify the preciseness of our prediction in part by the information of other data source.