Abstract
Given the sequences of an RNA and a protein as input, a biologist may wish to know whether or not the RNA-protein pair interact. If they interact, where are the interaction sites? Knowing the RNA binding sites often provide useful clues for the understanding of a variety of biological processes, developing the computational methods to address these questions can be really helpful. In this study, we use features including Pseudo Position-Specific Score Matrix (PsePSSM) computed by PSI-BLAST and Dipeptide Composition (DC) as feature vectors. Then, the Knearest neighbor (K-NN) and Support Vector Machine (SVM) classifiers are employed to identify the residues that interact with RNA in RNA-binding protein. Our experiments show that the above methods are used effectively to deal with this complicated problem of predicting RNA-protein interaction and interaction sites.
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