MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning | |
Zhao, BW (Zhao, Bo-Wei)[ 1,2,3 ]; You, ZH (You, Zhu-Hong)[ 1,2,3 ]; Wong, L (Wong, Leon)[ 1,2,3 ]; Zhang, P (Zhang, Ping)[ 4 ]; Li, HY (Li, Hao-Yuan)[ 5 ]; Wang, L (Wang, Lei)[ 1,2,3 ] | |
刊名 | FRONTIERS IN GENETICS |
2021 | |
卷号 | 12期号:4页码:1-8 |
关键词 | drug disease drug repositioning multi-graph representation learning graph embedding |
ISSN号 | 1664-8021 |
DOI | 10.3389/fgene.2021.657182 |
英文摘要 | Drug repositioning is an application-based solution based on mining existing drugs to find new targets, quickly discovering new drug-disease associations, and reducing the risk of drug discovery in traditional medicine and biology. Therefore, it is of great significance to design a computational model with high efficiency and accuracy. In this paper, we propose a novel computational method MGRL to predict drug-disease associations based on multi-graph representation learning. More specifically, MGRL first uses the graph convolution network to learn the graph representation of drugs and diseases from their self-attributes. Then, the graph embedding algorithm is used to represent the relationships between drugs and diseases. Finally, the two kinds of graph representation learning features were put into the random forest classifier for training. To the best of our knowledge, this is the first work to construct a multi-graph to extract the characteristics of drugs and diseases to predict drug-disease associations. The experiments show that the MGRL can achieve a higher AUC of 0.8506 based on five-fold cross-validation, which is significantly better than other existing methods. Case study results show the reliability of the proposed method, which is of great significance for practical applications. |
WOS记录号 | WOS:000641977800001 |
内容类型 | 期刊论文 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7813] |
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)[ 1,2,3 ] |
作者单位 | 1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou, Jiangsu, Peoples R China 2.BaoJi Univ Arts & Sci, Sch Comp Sci, Baoji, Peoples R China 3.Xinjiang Lab Minor Speech & Language Informat Pro, Urumqi, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, BW ,You, ZH ,Wong, L ,et al. MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning[J]. FRONTIERS IN GENETICS,2021,12(4):1-8. |
APA | Zhao, BW ,You, ZH ,Wong, L ,Zhang, P ,Li, HY ,&Wang, L .(2021).MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning.FRONTIERS IN GENETICS,12(4),1-8. |
MLA | Zhao, BW ,et al."MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning".FRONTIERS IN GENETICS 12.4(2021):1-8. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论