中国媒介生物学及控制杂志 ›› 2018, Vol. 29 ›› Issue (3): 309-312.DOI: 10.11853/j.issn.1003.8280.2018.03.025

• 调查研究 • 上一篇    下一篇

传染病控制中基因组大数据管理的初步构建

阳波, 王海涛, 张婷婷, 张雯, 曹立娜, 李文平, 罗成旺   

  1. 中国疾病预防控制中心传染病预防控制所设备条件处, 生物信息室, 北京 102206
  • 收稿日期:2018-05-16 出版日期:2018-06-20 发布日期:2018-06-20
  • 通讯作者: 罗成旺,Email:luochengwang@icdc.cn
  • 作者简介:阳波,男,助理研究员,主要从事疾病控制和仪器设备配置与疾病控制能力建设工作,Email:yangbo@icdc.cn

A study on construction of big data management in infectious disease control

YANG Bo, WANG Hai-tao, ZHANG Ting-ting, ZHANG Wen, CAO Li-na, LI Wen-ping, LUO Cheng-wang   

  1. National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
  • Received:2018-05-16 Online:2018-06-20 Published:2018-06-20

摘要: 目的 探讨基因组大数据管理架构,提升传染病控制中基因组大数据管理水平。方法 收集和参考传染病控制领域基因组大数据的重要科技文献以及政策性资料,采用Delphi法咨询相关专家总结归纳管理要素,建设信息化的管理平台。结果 初步构建数据管理方案、试剂耗材及相关服务采购管理信息平台和微生物基因组数据库等协同管理体系,采购管理平台由管理部门、业务部门和测序服务公司组成,并与基因组数据库关联,进行数据的审核、验收和分析,做到数据及时更新和共享,比传统的审核流程快8~9 d。制定平台的基本框架和功能分区,改变其粗放式管理传统做法,提高了科研工作效率。结论 基因组大数据管理体系有利于加强平台管理的信息化、规范化及专业化建设,为课题的结题和审计提供统计数据,提升服务保障功能。

关键词: 传染病, 基因组, 大数据

Abstract: Objective To explore the management framework of genomic big data and to better serve infectious disease outbreak investigation and public health surveillance. Methods Scientific and legislative papers in the areas of genomic epidemiology and genomics in public health were extensively collected and reviewed. The Delphi method was used to consult experts on the summarization of the management factors and construction of information management platform. Results The collaborative management system including data management scheme, reagent and consumables information management platform and microbial genome database was constructed preliminarily. The reagent and consumables information management platform consisted of management department, laboratory department and company, which was connected to the genome database. It would keep data updated and shared in a timely manner. It could be 8-9 days faster than the traditional management model. The basic framework and functional division of the two platforms were drafted. It has set up to change its traditional extensive management and greatly improved the efficiency of scientific research. Conclusion The management of big genome data should be helpful to strengthen the management with informatization, standardization and specialization. It would provide statistical data for other projects, as well as audit department and enhance the service function.

Key words: Infectious disease, Genome, Big data

中图分类号: