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数据分析与知识发现  2018, Vol. 2 Issue (1): 1-8    DOI: 10.11925/infotech.2096-3467.2017.1330
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
面向精准医学知识发现的生物医学信息学发展*
张志强1(),范少萍2,陈秀娟1,3
1(中国科学院成都文献情报中心 成都 610041)
2(中国医学科学院医学信息研究所 北京 100020)
3(中国科学院大学 北京 100049)
Biomedical Informatics Studies for Knowledge Discovery in Precision Medicine
Zhiqiang Zhang1(),Shaoping Fan2,Xiujuan Chen1,3
1(Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041, China)
2(Institute of Medical Information & Library, Chinese Academy of Medical Sciences, Beijing 100020, China)
3(University of Chinese Academy of Sciences, Beijing 100049, China)
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摘要 

目的】了解并梳理大数据驱动的知识发现新范式下, 生物医学信息学的最新进展, 并给出生物医学信息学未来发展的建议。【方法】通过文献调研与平台试用, 总结近几年生物医学信息学在大数据资源体系建设、数据分析平台、数据分析方法、辅助临床决策应用等方面的发展现状。【结果】未来可将加强生物医学大数据体系建设、创新大数据分析基础理论与方法研究、推进知识分析工具与平台开发、促进临床转化应用以及培养高层次专门人才等作为生物医学信息学的重点发展方面。【局限】限于篇幅, 未全面涉及生物医学数据资源、方法与应用案例等。【结论】本文针对精准医学大数据知识发现环境下生物医学信息学发展提出5方面建议, 可辅助该学科进一步顺应科学大数据的发展趋势, 满足领域知识发现的需求。

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张志强
范少萍
陈秀娟
关键词 精准医学生物医学信息学数据资源建设知识发现数据平台临床决策应用    
Abstract

[Objective] This paper reviews the latest Biomedical Informatics studies and indicates some future directions for data-driven knowledge discovery in precision medicine. [Methods] We summarized the developments of data resources, data analysis platforms and methods, clinical decision-making applications in Biomedical Informatics through literature review and service trials. [Results] Future directions of Biomedical Informatics include building better big data management system, proposing theories and methods for big data analysis, developing new tools and platforms, clinical application of research findings, as well as training senior personnel. [Limitations] More biomedical data resources, methods, and case studies should be added. [Conclusions] This study identifies the future developments of Biomedical Informatics in precision medicine, which utilizes big data analytics to discover more knowledge.

Key wordsPrecision Medicine    Biomedical Informatics    Data Resources Construction    Knowledge Discovery    Data Platform    Clinical Decision Application
收稿日期: 2017-12-27     
基金资助:*本文系国家社会科学基金重点项目“面向领域知识发现的学科信息学理论与应用研究”(项目编号:17ATQ008)和国家自然科学基金青年项目“面向精准医学的基因-疾病-药物语义关系抽取研究”(项目编号: 71704188)的研究成果之一
引用本文:   
张志强,范少萍,陈秀娟. 面向精准医学知识发现的生物医学信息学发展*[J]. 数据分析与知识发现, 2018, 2(1): 1-8.
Zhiqiang Zhang,Shaoping Fan,Xiujuan Chen. Biomedical Informatics Studies for Knowledge Discovery in Precision Medicine. Data Analysis and Knowledge Discovery, DOI:10.11925/infotech.2096-3467.2017.1330.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.1330
数据库名称 数据量 年增长量
PubMed 26 413 966 4.7%
MeSH 265 382 2.4%
ClinVar 159 184 27.4%
dbVar 6 147 903 37.2%
SNP 819 309 474 16.1%
Taxonomy 1 617 350 13.3%
Gene 24 351 351 13.8%
Protein 307 799 547 37.7%
PubChem Compound 91 679 397 50.9%
表1  NCBI部分数据库的数据量及增长量(截至2016年9月3日)[12]
图1  GenBank数据库Base和Sequences数据变化情况[13]
图2  DrugBank数据库中包含的数据量(截至2017年9月)[14]
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