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Signal peptides are short regions of amino acid residues, which have become a crucial tool in finding new drugs or reprogramming cells for gene therapy. Owing to the rapidly increasing number of protein, it is highly demanded to develop the automated algorithm to identify the signal peptides. Recently, we had adopted a new alignment kernel function to identify secretory proteins. Compared with previous...
Determination of protein structural class is a quite meaningful topic in protein science, because a priori knowledge of a protein structural class can provide useful information about its overall structure. The results of most previous studies used high homologous dataset with four structural classes should not be perceived as reliable, because the sequence homology has very significant impact on...
Evolutionary conservation estimated from a multiple sequence alignment is a powerful indicator of the functional significance of a residue, and helps to predict active sites, ligand binding sites, and protein interaction interfaces. Many algorithms that calculate conservation work well provided better and balanced alignment are used. Such a strong dependence on the alignment makes the results highly...
The sliding window method will cause the severe unbalanced dataset problem. In this paper, under-sample the majority class method is adopted to solve this problem, and SVM is used to classify the processed data. The better prediction result of minority class (that is, the signal peptides positive sample set) is observed. Besides, we discover that the (-3,-1) rule is helpful to the prediction. So Information...
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