A new technique for selecting features from protein sequences
A new method for selecting features from protein sequences is proposed in this paper. First, the protein sequences are converted into fixed-dimensional feature vectors. Then, a subset of features is selected using relative entropy method and used as the inputs for Support Vector Machine (SVM). Finally, the trained SVM classifier is utilized to classify protein sequences into certain known protein families. Experimental results over proteins obtained from PlR database and GPCRs have shown that our proposed approach is really effective and efficient in selecting features from protein sequences.
relative entropy support vector machine feature extraction protein sequence classification