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Tissue specific prediction of N6-methyladenine sites based on an ensemble of multi-input hybrid neural network

CANGZHI JIA1, DONG JIN1, XIN WANG1, QI ZHAO2,*

1 School of Science, Dalian Maritime University, Dalian, 116026, China
2 School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China

* Corresponding Author:QI ZHAO. Email: email

BIOCELL 2022, 46(4), 1105-1121. https://doi.org/10.32604/biocell.2022.016655

Abstract

N6-Methyladenine is a dynamic and reversible post translational modification, which plays an essential role in various biological processes. Because of the current inability to identify m6A-containing mRNAs, computational approaches have been developed to identify m6A sites in DNA sequences. Aiming to improve prediction performance, we introduced a novel ensemble computational approach based on three hybrid deep neural networks, including a convolutional neural network, a capsule network, and a bidirectional gated recurrent unit (BiGRU) with the self-attention mechanism, to identify m6A sites in four tissues of three species. Across a total of 11 datasets, we selected different feature subsets, after optimized from 4933 dimensional features, as input for the deep hybrid neural networks. In addition, to solve the deviation caused by the relatively small number of experimentally verified samples, we constructed an ensemble model through integrating five sub-classifiers based on different training datasets. When compared through 5-fold cross-validation and independent tests, our model showed its superiority to previous methods, im6A-TS-CNN and iRNA-m6A.

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APA Style
JIA, C., JIN, D., WANG, X., ZHAO, Q. (2022). Tissue specific prediction of n6-methyladenine sites based on an ensemble of multi-input hybrid neural network. BIOCELL, 46(4), 1105-1121. https://doi.org/10.32604/biocell.2022.016655
Vancouver Style
JIA C, JIN D, WANG X, ZHAO Q. Tissue specific prediction of n6-methyladenine sites based on an ensemble of multi-input hybrid neural network. BIOCELL . 2022;46(4):1105-1121 https://doi.org/10.32604/biocell.2022.016655
IEEE Style
C. JIA, D. JIN, X. WANG, and Q. ZHAO "Tissue specific prediction of N6-methyladenine sites based on an ensemble of multi-input hybrid neural network," BIOCELL , vol. 46, no. 4, pp. 1105-1121. 2022. https://doi.org/10.32604/biocell.2022.016655



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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