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Knowledge Graph-based Neurodegenerative Diseases and Diet Relationship Discovery

2021-09-13 · Yi Nian, Jingcheng Du, Larry Bu, Fang Li, Xinyue Hu, Yuji Zhang, Cui Tao

To date, there are no effective treatments for most neurodegenerative diseases. However, certain foods may be associated with these diseases and bring an opportunity to prevent or delay neurodegenerative progression. Our objective is to construct a knowledge graph for neurodegenerative diseases using literature mining to study their relations with diet. We collected biomedical annotations (Disease, Chemical, Gene, Species, SNP&Mutation) in the abstracts from 4,300 publications relevant to both neurodegenerative diseases and diet using PubTator, an NIH-supported tool that can extract biomedical concepts from literature. A knowledge graph was created from these annotations. Graph embeddings were then trained with the node2vec algorithm to support potential concept clustering and similar concept identification. We found several food-related species and chemicals that might come from diet and have an impact on neurodegenerative diseases.

📄 PDF Abstract BibTeX arXiv:2109.06123

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Literature Mining

Methods 이 논문이 사용한 방법론

node2vec node2vec is a framework for learning graph embeddings for nodes in graphs. Node2vec maximizes a likelihood objective over mappings which preserve neighbourhood distances in…

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