A Novel Prediction Method for ATP-Binding Sites From Protein Primary Sequences Based on Fusion of Deep Convolutional Neural Network and Ensemble Learning

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 s...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.21485-21495
Hauptverfasser:	Song, Jiazhi, Liang, Yanchun, Liu, Guixia, Wang, Rongquan, Sun, Liyan, Zhang, Ping
Format:	Artikel
Sprache:	eng
Schlagworte:	Adenosine Algorithms Annotations Artificial neural networks Benchmarks Binding sites Classification Computer architecture Convolutional neural networks Datasets deep convolutional neural network Deep learning Ensemble learning Feature extraction inception neural network Machine learning Neural networks Prediction methods protein primary sequence Protein sequence Protein-ATP binding sites prediction Proteins Solvents Source code
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