实验动物与比较医学 ›› 2026, Vol. 46 ›› Issue (3): 416-425.DOI: 10.12300/j.issn.1674-5817.2025.136

• 实验动物设施及管理 • 上一篇    下一篇

斑马鱼品系及斑马鱼鱼房的自动化管理

卜纪雯1()(), 华叶2, 金仕容2, 任宁欣1, 李福宁1, 杜久林1   

  1. 1.中国科学院脑科学与智能技术卓越创新中心感觉整合与行为研究组, 上海 200031
    2.中国科学院脑科学与智能技术卓越创新中心全脑介观神经联接图谱研究平台(斑马鱼), 上海 200031
  • 收稿日期:2025-08-19 修回日期:2025-12-05 出版日期:2026-06-25 发布日期:2026-06-19
  • 通讯作者:
    卜 纪 雯(1982—),女,硕 士,高 级 实 验 师,研 究 方 向:分 子 发 育 生 物 学。E-mail: jwbu@ion.ac.cn。ORCID:0009-0006-0933-7314。
  • 作者简介:华 叶(1983—),女,硕士,助理研究员,研究方向:斑马鱼早胚发育与精子发生。E-mail: ye.hua@ion.ac.cn
    金仕容(1994—),女,硕士,实验师,研究方向:水产养殖。E-mail:18817772747@163.com
  • 基金资助:
    国家自然科学基金创新研究群体项目“全脑尺度感觉-运动转导的神经机制”(32321003)

Automated Management of Zebrafish Strains and Zebrafish Facilities

BU Jiwen1()(), HUA Ye2, JIN Shirong2, REN Ningxin1, LI Funing1, DU Jiulin1   

  1. 1.Laboratory of Sensory Integration & Behavior, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
    2.Research Platform of Whole Brain Mesoscopic Neural Junction Map (Zebrafish), Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
  • Received:2025-08-19 Revised:2025-12-05 Published:2026-06-25 Online:2026-06-19
  • Contact: BU Jiwen (ORCID: 0009-0006-0933-7314), E-mail: jwbu@ion.ac.cn

摘要:

目的 通过提升斑马鱼品系及斑马鱼鱼房管理效率,变革依赖人力的传统管理范式,推动管理模式从传统人工操作向标准化、数字化、自动化与精细化全面转型,从而显著提升管理质量与工作效率。 方法 中国科学院脑科学与智能技术卓越创新中心感觉整合与行为研究组自主开发了斑马鱼房及品系自动化管理系统V1.0(软著登记号:2021SR0236837),该系统完整记录了斑马鱼鱼房全部运行数据及斑马鱼品系完整数据。基于以上数据的深度挖掘成果并结合管理经验,将管理规定转化为可执行的系统指令集,构建了“监测―分析―预警―任务派发―执行―记录”的全流程自动化管理闭环。 结果 本管理系统已稳定运行5年,成功应用于3个斑马鱼鱼房,累计支持78名科研人员,高效管理了1 108个质粒和1 123个斑马鱼品系,其中291个品系已纳入斑马鱼精子库。采用利克特量表(Likert scale)对28名核心用户进行使用调研,4个大类共计14个评估维度的平均分为4.46~4.89分,均远高于中间值(3分),表明用户对系统的各维度均给予高度评价。同时,大多数维度的标准差处于较低水平(s ≤ 0.44),反映出用户评价具有良好的一致性。 结论 本研究融合信息技术、大数据分析和现代管理理念,实现了斑马鱼鱼房管理中“数据采集―分析执行―系统优化”的良性循环,显著提升了斑马鱼鱼房的管理效率与精细化水平,推动了管理模式向自动化转型发展。

关键词: 斑马鱼, 斑马鱼鱼房, 信息化管理系统, 大数据分析, 自动化管理

Abstract:

Objective This study aims to improve the management efficiency of zebrafish strains and zebrafish facilities and to transform the traditional management model that relies on manual labor. The goal is to promote a comprehensive transition from traditional manual operation to standardized, digitalized, automated, and refined management, thereby significantly improving management quality and work efficiency. Methods The research group independently developed the "Zebrafish Facility and Zebrafish Strain Automation Management System V1.0" (Software Copyright Registration No. 2021SR0236837), which comprehensively recorded all operational data of the zebrafish facilities and completed data on zebrafish strains. By combining in-depth mining of these data with management experience, management regulations were transformed into executable system instruction sets, and a full-process automated closed-loop management framework of "Monitoring–Analysis–Early Warning–Task Assignment–Execution–Recording" was established. Results This management system has been operating stably for 5 years and has been successfully applied in 3 zebrafish facilities, cumulatively supporting 78 researchers and efficiently managing 1 108 plasmids and 1 123 zebrafish strains, among which 291 strains has been incorporated into zebrafish sperm bank management. A Likert scale survey of 28 core users covering 14 evaluation dimensions across 4 major categories showed average scores of 4.46–4.89, all far above the midpoint (3 points) of the scale, indicating that users gave high evaluations to all dimensions of the system. Meanwhile, the standard deviations of most dimensions were low (s ≤ 0.44), reflecting good consistency in user evaluations. Conclusion This study integrates information technology, big data analysis, and modern management concepts to achieve a virtuous cycle of "data collection–analysis and execution–system optimization" in zebrafish facility management. It significantly improves management efficiency and refinement and promotes the development of management models toward automation.

Key words: Zebrafish, Zebrafish facility, Information management system, Big data analysis, Automated management

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