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Protein-RNA interactions play a critical role in various biological processes. The accurate prediction of RNA-binding residues in proteins has been one of the most challenging and intriguing problems in the field of computational biology. The existing methods still have a relatively low accuracy especially for the sequence based ab-initio methods. In this work, we propose an approach aPRBind, a convolutional neural network (CNN)-based ab-initio method for RNA-binding residue prediction. aPRBind is trained with sequence features and struc
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