Mining latent relations between disease and transcription factor based on knowledge graph: a case study on Alzheimer's Disease | |
Hu ZY(胡正银)1,2![]() ![]() | |
2020-11 | |
Conference Name | 10th Global TechMining Conference |
Source Publication | 10th Global TechMining Conference |
Issue | 0 |
Conference Date | 2020.11.11-13 |
Conference Place | virtual event |
Abstract | Transcription factor (TF) is a general term for a variety of proteins or genes that regulate gene expression, which controls the activity of a gene by determining whether the gene’s DNA is transcribed into RNA. Alzheimer's Disease (AD) is a kind of neurodegenerative diseases which are associated with abnormal gene expression. However, the direct relations from literatures between TF and AD are very weak. This study aims to mining the latent relations between TF and AD by knowledge graph and semantic path analytics based on Literature-based discovery (LBD). Firstly, Subject-Predicate-Object (SPO) triples related are retrieved to construct a domain KG. Then, semantic paths with predications are extracted from KG using path traversal algorithm. After that we mine these semantic paths from four respects to reveal latent relations between TF and AD: key concepts identification, paths strength measurement and ranking, paths clustering, and emerging intermediate concepts prediction. Finally, the latent relations will be visualized and interpreted. The study is in process and more details could be presented on the conference. It will help inspire research ideas and make new discoveries to scientists. |
Document Type | 会议论文 |
Identifier | http://ir.las.ac.cn/handle/12502/11366 |
Collection | 中国科学院成都文献情报中心_信息技术部 |
Affiliation | 1.中国科学院成都文献情报中心 2.中国科学院大学经济管理学院图书情报与档案管理系 3.悉尼科技大学 4.中国科学院广州生物医药与健康研究院 |
First Author Affilication | 中国科学院文献情报中心 |
Recommended Citation GB/T 7714 | Hu ZY,Dai B,Zhang Yi,et al. Mining latent relations between disease and transcription factor based on knowledge graph: a case study on Alzheimer's Disease[C],2020. |
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