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Accurately identifying protein-ATP (Adenosine-5'-triphosphate) binding sites is significant for protein function annotation and new drug invention. Previous studies often utilize classical machine learning classification algorithms to predict protein-ATP binding sites based on protein primary sequence. However, deep learning as a newly developed technique has shown outstanding performance in various fields. In this work, we introduce the deep convolutional neural network for protein-ATP bindingdoi:10.1109/access.2020.2968847 fatcat:4hlrw27zevcmrnbdylffzlsvk4