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An integrated platform for Brucella with knowledge graph technology: From genomic analysis to epidemiological projection

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机构: [1]West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. [2]College of Computer Science, Sichuan University, Chengdu, China. [3]China Animal Health and Epidemiology Center, Qingdao, Shandong, China. [4]Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China. [5]Med-X Center for Informatics, Sichuan University, Chengdu, China. [6]Shanghai Artificial Intelligence Laboratory, Shanghai, China. [7]Hainan Institute of Zhejiang University, Sanya, China. [8]Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China. [9]Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China.
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Motivation: Brucella, the causative agent of brucellosis, is a global zoonotic pathogen that threatens both veterinary and human health. The main sources of brucellosis are farm animals. Importantly, the bacteria can be used for biological warfare purposes, requiring source tracking and routine surveillance in an integrated manner. Additionally, brucellosis is classified among group B infectious diseases in China and has been reported in 31 Chinese provinces to varying degrees in urban areas. From a national biosecurity perspective, research on brucellosis surveillance has garnered considerable attention and requires an integrated platform to provide researchers with easy access to genomic analysis and provide policymakers with an improved understanding of both reported patients and detected cases for the purpose of precision public health interventions. Results: For the first time in China, we have developed a comprehensive information platform for Brucella based on dynamic visualization of the incidence (reported patients) and prevalence (detected cases) of brucellosis in mainland China. Especially, our study establishes a knowledge graph for the literature sources of Brucella data so that it can be expanded, queried, and analyzed. When similar "epidemiological comprehensive platforms" are established in the distant future, we can use knowledge graph to share its information. Additionally, we propose a software package for genomic sequence analysis. This platform provides a specialized, dynamic, and visual point-and-click interface for studying brucellosis in mainland China and improving the exploration of Brucella in the fields of bioinformatics and disease prevention for both human and veterinary medicine.Copyright © 2022 Ma, Xiao, Zhu, Jiang, Jiang, Zhang, Li, Yue and Zhang.

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出版当年[2022]版:
大类 | 3 区 生物学
小类 | 3 区 遗传学
最新[2023]版:
大类 | 3 区 生物学
小类 | 3 区 遗传学
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第一作者机构: [1]West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
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通讯机构: [2]College of Computer Science, Sichuan University, Chengdu, China. [8]Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, China. [9]Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China.
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