.png){kind=icon}
返回
Network embedding in biomedical data science
.png){kind=icon}
PRE
AI
DOI：10.1093/bib/bby117.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Owning to the rapid development of computer technologies, an increasing number of relational data have been emerging in modern biomedical research. Many network-based learning methods have been proposed to perform analysis on such data, which provide people a deep understanding of topology and knowledge behind the biomedical networks and benefit a lot of applications for human healthcare. However, most network-based methods suffer from high computational and space cost. There remain challenges on handling high dimensionality and sparsity of the biomedical networks. The latest advances in network embedding technologies provide new effective paradigms to solve the network analysis problem. It converts network into a low-dimensional space while maximally preserves structural properties. In this way, downstream tasks such as link prediction and node classification can be done by traditional machine learning methods. In this survey, we conduct a comprehensive review of the literature on applying network embedding to advance the biomedical domain. We first briefly introduce the widely used network embedding models. After that, we carefully discuss how the network embedding approaches were performed on biomedical networks as well as how they accelerated the downstream tasks in biomedical science. Finally, we discuss challenges the existing network embedding applications in biomedical domains are faced with and suggest several promising future directions for a better improvement in human healthcare.
Keyword:
biomedical networks
biomedical knowledge graphs
biomedical informatics
network embedding
graph embedding
network-based learning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.7
论文数:
5.8K
被引数:
2.7W
机构
引用论文
Network embedding-based representation learning for single cell RNA-seq data.png)
NUCLEIC ACIDS RESEARCH
OAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏DBpedia - A large-scale, multilingual knowledge base extracted from WikipediaDBpedia-从维基百科中提取的大规模多语言知识库SEMANTIC WEBOAAI
SEMANTIC WEBIF2.9
OAAI分享收藏
查看更多内容