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主管单位 工业和信息化部 主办单位 哈尔滨工业大学 主编 任南琪 国际刊号ISSN 1672-5565 国内刊号CN 23-1513/Q

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引用本文:HE Yongqun,余红,杨啸林,邵晨,周伟,朱彦,王海河,刘清平,谢江安,ZHENG Jie,朱伟民.本体:生物医学大数据与精准医学研究的基础[J].生物信息学,2018,16(1):7-14.
HE Yongqun,YU Hong,YANG Xiaolin,SHAO Chen,ZHOU Wei,ZHU Yan,WANG Haihe,LIU Qingping,XIE Jiangan,ZHENG Jie,ZHU Weimin.Ontology:Foundation of biomedical big data and precision medicine research[J].Chinese Journal of Bioinformatics,2018,16(1):7-14.
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本体:生物医学大数据与精准医学研究的基础
HE Yongqun 1,2,余红3,杨啸林1,邵晨1,周伟4,朱彦5,王海河6,刘清平7,谢江安8,ZHENG Jie 9, 朱伟民10
(1. 中国医学科学院 基础医学研究所,北京 100005; 2. University of Michigan Medical School, Ann Arbor, MI, 48109 USA ; 3. 贵州大学医学院,贵州省人民医院,贵阳550002;4. 国家人口与健康科学数据共享服务平台,北京100700; 5. 中国中医科学院 中医药信息研究所,北京100700;6. 哈尔滨医科大学大庆校区,黑龙江, 大庆 163319; 7. 广州中医药大学,广州510000;8. 重庆邮电大学,重庆400065;9. University of PennsylvaniaPerelman School of Medicine, PA, 19104 USA ; 10. 国家蛋白质科学中心北京凤凰中心,北京102206)
摘要:
在最近兴起的生物医学大数据和精准医学研究中,本体正发挥着不可替代的作用。但一大部分人对本体的定义、类型与应用比较混淆。这篇综述对这些问题进行了回答。具体而言,本体使用人和计算机都可以理解的术语及关系集来表述各种实体/概念以及它们之间关系。根据本体的作用,本体可分为三类:具有多关系模型的增强版控制术语集,反映某知识域的本体知识系统,和对元数据在语义上的约束与标准化的元数据本体。基于这些作用,本体被广泛地应用于生物医学数据的标准化、整合、检索与分析,已经知识的挖掘。当代本体学的研究发展迅速,我国刚刚起步,机遇与挑战并存。广泛地开展国内与国际有关本体的合作研究,将促进国内生物医学本体领域研究水平的整体提升,提高生物与临床科研大数据整合与精准医学研究的能力。
关键词:  可控词表  本体  基因本体  生物医学大数据  精准医学  本体中国
DOI:10.3969/j.issn.1672-5565.201710006
分类号:R318
文献标识码:A
基金项目:美国NIH LINCS (U54HL127624)eDSR课题;贵阳市科技计划筑科合同(20151001 社78号, 20161001号);北京市自然科学基金资助项目(7174328);国家重点研发计划资助(2017YFC0908404);及国际科技合作专项(S2014ZR0005).
Ontology:Foundation of biomedical big data and precision medicine research
HE Yongqun 1,2, YU Hong 3, YANG Xiaolin 1, SHAO Chen 1, ZHOU Wei 4, ZHU Yan 5, WANG Haihe 6, LIU Qingping 7, XIE Jiangan 8, ZHENG Jie 9, ZHU Weimin 10
(1. Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing 100700, China;2. University of Michigan Medical School, Ann Arbor, MI 48109, USA; 3. Guizhou University Medical College, Guizhou Province People’s Hospital, Guiyang 550002, China; 4. National Scientific Data Sharing Platform for Population and Health, Beijing 100700, China; 5. Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences, Beijing 100700, China; 6. Daqing Branch of Harbin Medical University, Daqing 163319, China; 7. Guangzhou University of Chinese Medicine, Guangzhou, 510000, China; 8. Chongqing University of Posts and Telecommunications, Chongqing 400065, China; 9. University of Pennsylvania Perelman School of Medicine, PA 19104, USA; 10. The National Center for Protein Sciences,Beijing 102206, China)
Abstract:
Ontology plays an unreplaceable role in the recently emerging big data and precision medicine research. However, the definition, subtypes and applications of ontology remain unclear for the majority of researchers. The goal of this review is to address these issues. Specifically, an ontology is a set of human- and computer readable terms, or concepts, and the relations that represent entities and their relationships in a specific domain. Based on functions, ontologies can be classified into three types: as an enhanced controlled terminology with multiple relational types, as a knowledge base abstracted from a specific real-life domain, and as a metadata ontology for metadata standardization. These types of ontologies have been widely used in biomedical domains for data standardization, integration, query and analysis, as well as for information transformation and knowledge mining. Researches on biomedical ontology have witnessed a fast progress worldwide in the last decade. As a late starter, China faces both opportunities and challenges in its ontology researches and applications. A collaboration between Chinese and international biomedical ontology communities is strongly suggested to elevate China’s national capacity for biological and clinical big data integration, and to facilitate precision medicine research.
Key words:  Controlled terminology  Ontology  Gene ontology  Biomedical big data  Precision medicine  Onto-China

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