Prediction of Drug-Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model | |
Chen, ZH (Chen, Zhan-Heng)[ 1,2 ]; You, ZH (You, Zhu-Hong)[ 1,2 ]; Guo, ZH (Guo, Zhen-Hao)[ 1,2 ]; Yi, HC (Yi, Hai-Cheng)[ 1,2 ]; Luo, GX (Luo, Gong-Xu)[ 1,2 ]; Wang, YB (Wang, Yan-Bin)[ 3 ] | |
刊名 | FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY |
2020 | |
卷号 | 8期号:6页码:1-9 |
关键词 | drug-target interactions molecular association network attribute feature behavior feature random forest |
ISSN号 | 2296-4185 |
DOI | 10.3389/fbioe.2020.00338 |
英文摘要 | Predicting drug-target interactions (DTIs) is crucial in innovative drug discovery, drug repositioning and other fields. However, there are many shortcomings for predicting DTIs using traditional biological experimental methods, such as the high-cost, time-consumption, low efficiency, and so on, which make these methods difficult to widely apply. As a supplement, thein silicomethod can provide helpful information for predictions of DTIs in a timely manner. In this work, a deep walk embedding method is developed for predicting DTIs from a multi-molecular network. More specifically, a multi-molecular network, also called molecular associations network, is constructed by integrating the associations among drug, protein, disease, lncRNA, and miRNA. Then, each node can be represented as a behavior feature vector by using a deep walk embedding method. Finally, we compared behavior features with traditional attribute features on an integrated dataset by using various classifiers. The experimental results revealed that the behavior feature could be performed better on different classifiers, especially on the random forest classifier. It is also demonstrated that the use of behavior information is very helpful for addressing the problem of sequences containing both self-interacting and non-interacting pairs of proteins. This work is not only extremely suitable for predicting DTIs, but also provides a new perspective for the prediction of other biomolecules' associations. |
WOS记录号 | WOS:000543092900001 |
内容类型 | 期刊论文 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7403] |
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 ] |
作者单位 | 1.Zhejiang Univ, Sch Cyber Sci & Technol, Hangzhou, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, ZH ,You, ZH ,Guo, ZH ,et al. Prediction of Drug-Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model[J]. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,2020,8(6):1-9. |
APA | Chen, ZH ,You, ZH ,Guo, ZH ,Yi, HC ,Luo, GX ,&Wang, YB .(2020).Prediction of Drug-Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model.FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,8(6),1-9. |
MLA | Chen, ZH ,et al."Prediction of Drug-Target Interactions From Multi-Molecular Network Based on Deep Walk Embedding Model".FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY 8.6(2020):1-9. |
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