首页|Fully Convolutional Neural Network for Predicting Cancer-Specific CircRNA-MiRNA Interaction Sites

Fully Convolutional Neural Network for Predicting Cancer-Specific CircRNA-MiRNA Interaction Sites

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In recent years, the research of circRNAs in biomedical fields has gained momentum, particularly in cancer biology where they play a crucial role. CircRNAs regulate gene expression by adsorbing miRNAs and acting as 'sponges'. Dysregulation of miRNAs has been observed in various cancer tissues, and co-expression of circRNAs with miRNAs has been noted in many cancer tissues. The co-expression of miRNAs with circRNAs may play an important role in regulating tumour growth. In this study, we predicted cancer-specific circRNA-miRNA interaction sites using a fully convolutional neural network model, and achieved high prediction accuracy by optimizing the model parameters. This study is significant for understanding the mechanism of circRNAs role in cancer development and developing related therapeutic and diagnostic methods.

cancercircrnamirnafully convolutional neural networkcircrna-mirna interaction

Wei Liu、JiaYing Wei、DiMing Wu、Ke Chen、Zhen Shen

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School of Computer and Software, Nanyang Institute of Technology, Changjiang Road 80, Nanyang 473004, Henan, China

School of Computer, China University of Geosciences(Wuhan), Lumo Road 388, Wuhan 430070, Hubei, China

International Conference on advanced intelligent computing in bioinformatics

Tianjin(CN)

Advanced intelligent computing in bioinformatics

155-163

2024