Predicting protein function at the proteomic-scale is one of the fundamental goals in cell biology and proteomics. In this paper, we proposed a new method for characterizing protein sequences-the Weighted Segmented Pseudo-amino acid composition Moment Vector (W-SPsAA-MV). From protein sequences, the encoding method of W-SPsAA-MV is applied to protein functional class prediction associated with the nearest neighbor algorithm (NNA) and covariant discriminant (CD) classifier. The experiment results show that our new method is efficient to predict functional class of q...
