GANCDA: a novel method for predicting circRNA-disease associations based on deep generative adversarial network | |
Yan, X (Yan, Xin)[ 1 ]; Wang, L (Wang, Lei)[ 2,3 ]; You, ZH (You, Zhu-Hong)[ 3 ]; Li, LP (Li, Li-Ping)[ 3 ]; Zheng, K (Zheng, Kai)[ 4 ] | |
刊名 | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS |
2020 | |
卷号 | 23期号:3页码:265-283 |
关键词 | circular RNA diseases CircRNA-disease association generative adversarial network logistic model tree |
ISSN号 | 1748-5673 |
DOI | 10.1504/IJDMB.2020.107880 |
英文摘要 | Circular RNA (circRNA) plays a key regulatory role in life activities. Recognising the association between circRNA and disease is of great significance for the study of disease mechanism. However, traditional experimental methods for identifying the association between circular RNA and disease are usually extremely blind and time consuming. Therefore, the method based on intelligent computing is needed to effectively predict the potential circRNA-disease association and narrow the identification range for biological experiments. In this paper, we propose a model GANCDA based on multi-source similar information and deep Generative Adversarial Network (GAN) to predict disease associated circRNA. The fivefold cross-validation of GANCDA on the circR2Disease dataset achieved 90.6% AUC, 89.2% accuracy and 89.4% precision. Moreover, GANCDA prediction results are also supported by biological experiments. These excellent results show that GANCDA can accurately predict the potential circRNA-disease association and can be used as an effective assistant tool for biological experiments. |
WOS记录号 | WOS:000551924900005 |
内容类型 | 期刊论文 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7686] |
专题 | 新疆理化技术研究所_多语种信息技术研究室 |
通讯作者 | You, ZH (You, Zhu-Hong)[ 3 ] |
作者单位 | 1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China 2.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Beijing 830011, Peoples R China 3.Zaozhuang Univ, Coll Informat Sci & Engn, Zaozhuang 277100, Shandong, Peoples R China 4.Zaozhuang Univ, Sch Foreign Languages, Zaozhuang 277100, Shandong, Peoples R China |
推荐引用方式 GB/T 7714 | Yan, X ,Wang, L ,You, ZH ,et al. GANCDA: a novel method for predicting circRNA-disease associations based on deep generative adversarial network[J]. INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS,2020,23(3):265-283. |
APA | Yan, X ,Wang, L ,You, ZH ,Li, LP ,&Zheng, K .(2020).GANCDA: a novel method for predicting circRNA-disease associations based on deep generative adversarial network.INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS,23(3),265-283. |
MLA | Yan, X ,et al."GANCDA: a novel method for predicting circRNA-disease associations based on deep generative adversarial network".INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS 23.3(2020):265-283. |
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