MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm
文献类型:期刊论文
作者 | Guo,ZH (Guo, Zhen-Hao) 1; You,ZH (You,Zhu-Hong) 1, 2; Huang,DS (Huang, De-Shuang) 3, 4; Yi, HC (Yi, Hai-Cheng) 2; Zheng, K (Zheng, Kai) 5; Chen, ZH (Chen, Zhan-Heng) 1; Wang, YB (Wang, Yan-Bin) 6 |
刊名 | BRIEFINGS IN BIOINFORMATICS |
出版日期 | 2021 |
卷号 | 22期号:2页码:2085-2095 |
ISSN号 | 1467-5463 |
关键词 | MeSHHeading2vecMeSH relationship networkgraph embeddingcomputational prediction model |
DOI | 10.1093/bib/bbaa037 |
英文摘要 | Effectively representing Medical Subject Headings (MeSH) headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify. In this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships), which can be constructed by the tree num. Then, five graph embedding algorithms including DeepWalk, LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed methods, we carried out the node classification and relationship prediction tasks. The results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the representation ability of vectors. Thus, it can serve as an input and continue to play a significant role in any computational models related to disease, drug, microbe, etc. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective. |
WOS记录号 | WOS:000642298000111 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7877] |
专题 | 新疆理化技术研究所_多语种信息技术研究室 |
作者单位 | 1.Zhejiang Univ, Hangzhou, Peoples R China 2.China Univ Min & Technol, Xuzhou, Jiangsu, Peoples R China 3.Tongji Univ, Inst Machines Learning & Syst Biol, Shanghai, Peoples R China 4.Tongji Univ, Shanghai, Peoples R China 5.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China 6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Guo,ZH ,You,ZH ,Huang,DS ,et al. MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm[J]. BRIEFINGS IN BIOINFORMATICS,2021,22(2):2085-2095. |
APA | Guo,ZH .,You,ZH .,Huang,DS .,Yi, HC .,Zheng, K .,...&Wang, YB .(2021).MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm.BRIEFINGS IN BIOINFORMATICS,22(2),2085-2095. |
MLA | Guo,ZH ,et al."MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm".BRIEFINGS IN BIOINFORMATICS 22.2(2021):2085-2095. |
入库方式: OAI收割
来源:新疆理化技术研究所
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