BMC Bioinformatics | |
Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks | |
Research | |
Libo Luo1  Hui Liu2  Ziheng Zhuang2  Jihong Guan3  Yinglong Song4  | |
[1] Changzhou NO. 7 People’s Hospital, 213011, Changzhou, Jiangsu, China;Changzhou NO. 7 People’s Hospital, 213011, Changzhou, Jiangsu, China;Changzhou University, 213164, Jiangsu, China;Department of Computer Science and Technology, Tongji University, 201804, Shanghai, China;Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University, 200433, Shanghai, China; | |
关键词: Drug positioning; Random walk; Heterogenous network; | |
DOI : 10.1186/s12859-016-1336-7 | |
来源: Springer | |
【 摘 要 】
BackgroundSince traditional drug research and development is often time-consuming and high-risk, there is an increasing interest in establishing new medical indications for approved drugs, referred to as drug repositioning, which provides a relatively low-cost and high-efficiency approach for drug discovery. With the explosive growth of large-scale biochemical and phenotypic data, drug repositioning holds great potential for precision medicine in the post-genomic era. It is urgent to develop rational and systematic approaches to predict new indications for approved drugs on a large scale.ResultsIn this paper, we propose the two-pass random walks with restart on a heterogenous network, TP-NRWRH for short, to predict new indications for approved drugs. Rather than random walk on bipartite network, we integrated the drug-drug similarity network, disease-disease similarity network and known drug-disease association network into one heterogenous network, on which the two-pass random walks with restart is implemented. We have conducted performance evaluation on two datasets of drug-disease associations, and the results show that our method has higher performance than six existing methods. A case study on the Alzheimer’s disease showed that nine of top 10 predicted drugs have been approved or investigational for neurodegenerative diseases. The experimental results show that our method achieves state-of-the-art performance in predicting new indications for approved drugs.ConclusionsWe proposed a two-pass random walk with restart on the drug-disease heterogeneous network, referred to as TP-NRWRH, to predict new indications for approved drugs. Performance evaluation on two independent datasets showed that TP-NRWRH achieved higher performance than six existing methods on 10-fold cross validations. The case study on the Alzheimer’s disease showed that nine of top 10 predicted drugs have been approved or are investigational for neurodegenerative diseases. The results show that our method achieves state-of-the-art performance in predicting new indications for approved drugs.
【 授权许可】
CC BY
© The Author(s) 2016
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202311093098090ZK.pdf | 1265KB | download | |
12864_2016_2682_Article_IEq34.gif | 1KB | Image | download |
12864_2016_3263_Article_IEq13.gif | 1KB | Image | download |
12864_2016_3263_Article_IEq14.gif | 1KB | Image | download |
12864_2016_3263_Article_IEq15.gif | 1KB | Image | download |
12864_2016_3263_Article_IEq17.gif | 1KB | Image | download |
12893_2017_312_Article_IEq1.gif | 1KB | Image | download |
12864_2016_2443_Article_IEq14.gif | 1KB | Image | download |
12864_2015_2055_Article_IEq66.gif | 1KB | Image | download |
12864_2017_4025_Article_IEq4.gif | 1KB | Image | download |
12864_2015_2198_Article_IEq41.gif | 1KB | Image | download |
12864_2015_2198_Article_IEq43.gif | 1KB | Image | download |
12864_2017_3498_Article_IEq1.gif | 1KB | Image | download |
12864_2017_4025_Article_IEq8.gif | 1KB | Image | download |
12864_2017_3708_Article_IEq1.gif | 1KB | Image | download |
12864_2017_4025_Article_IEq10.gif | 1KB | Image | download |
12864_2015_2055_Article_IEq77.gif | 1KB | Image | download |
12864_2015_2055_Article_IEq78.gif | 1KB | Image | download |
12864_2016_3440_Article_IEq35.gif | 1KB | Image | download |
12864_2015_2055_Article_IEq79.gif | 1KB | Image | download |
【 图 表 】
12864_2015_2055_Article_IEq79.gif
12864_2016_3440_Article_IEq35.gif
12864_2015_2055_Article_IEq78.gif
12864_2015_2055_Article_IEq77.gif
12864_2017_4025_Article_IEq10.gif
12864_2017_3708_Article_IEq1.gif
12864_2017_4025_Article_IEq8.gif
12864_2017_3498_Article_IEq1.gif
12864_2015_2198_Article_IEq43.gif
12864_2015_2198_Article_IEq41.gif
12864_2017_4025_Article_IEq4.gif
12864_2015_2055_Article_IEq66.gif
12864_2016_2443_Article_IEq14.gif
12893_2017_312_Article_IEq1.gif
12864_2016_3263_Article_IEq17.gif
12864_2016_3263_Article_IEq15.gif
12864_2016_3263_Article_IEq14.gif
12864_2016_3263_Article_IEq13.gif
12864_2016_2682_Article_IEq34.gif
【 参考文献 】
- [1]
- [2]
- [3]
- [4]
- [5]
- [6]
- [7]
- [8]
- [9]
- [10]
- [11]
- [12]
- [13]
- [14]
- [15]
- [16]
- [17]
- [18]
- [19]
- [20]
- [21]
- [22]
- [23]
- [24]
- [25]
- [26]
- [27]
- [28]
- [29]
- [30]
- [31]
- [32]