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DM-RPIs: Predicting ncRNA-protein interactions using stacked ensembling strategy
Affiliation:1. School of Information Engineering, East China Jiaotong University, Nanchang, China;2. College of Computer Science and Electronic Engineering, Hunan University, Changsha, China;3. College of Information Science and Engineering, Hunan Normal University, Changsha, China;4. School of Information Science and Engineering, Shandong Normal University, Jinan, China;1. Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China;2. Department of Biostatistics, School of Public Health, University of Texas Health Science Center, Houston, TX 77030, USA;1. School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China;2. Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230027, China;1. School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, China;2. Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230027, China;1. Department of Computer Engineering, Arak University, Arak, Iran;2. Bioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran;3. School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), P. O.Box 19395-5746, Tehran, Iran;4. Department of Computer Engineering, Islamic Azad University, Najafabad Branch, Najafabad, Tehran, Iran
Abstract:
Keywords:ncRNA-protein interactions  Deep Stacking Auto-encoders Networks (DSANs)  Support Vector Machine (SVM)  Random Forest (RF)  Convolution Neural Network (CNN)  Stacked integrate
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