Authors:
Dongsheng Zhao
1
;
Fan Tong
1
;
Zheheng Luo
2
;
Sheng Liu
3
and
Wei Song
3
Affiliations:
1
Information Center, Academy of Military Medical Sciences, Beijing, China
;
2
Information Department, No. 920 Hospital of PLA, Yunnan, China
;
3
Beijing MedPeer Information Technology Co., Ltd., Beijing, China
Keyword(s):
Gene, Mutation, Disease, Knowledge Graph, Platform.
Abstract:
In the era of precision medicine, clinicians need intensive and comprehensive evidence to conduct research and make decisions. However, current knowledge bases are isolated and lack integration with information from other databases or literature, constituting an obstacle for clinicians to locate and understand their interested relations. In this paper, we design a platform development methodology to construct and visualize a biomedical knowledge graph combining text mining tools and knowledge fusion models with web interface libraries. The platform thereby provides the functions of knowledge acquisition, integration, storage, search and visualization, where each concept in the relation is described by its properties, each relation in the database is located to sentences and each paragraph in the article is translated into Chinese. To further validate the feasibility and practicability, we applied the methodology to the “gene-mutation-disease” field and built a Biomedical Relation of
Gene-mUtation-diseasE (BROGUE) platform. The platform included 590 high-quality gene-mutation-disease relations covering a wide range of commonly-used gene (286), mutation (525) and disease (347) concepts by October 2019. Two tests demonstrated that BROGUE has potential to be useful for supporting biomedical research and clinical decisions. The platform has been deployed and is publicly available at http://brogue.medmdt.net/.
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