A qualitative study of the implementation of a bioinformatics tool in a biological research laboratory
A qualitative study of the implementation of a bioinformatics tool in a biological research laboratory
复制标题
DOI：
10.1016/j.ijmedinf.2006.09.022
复制
发表时间：
2007-11-01
影响因子：
4.9
通讯作者：
Tarczy-Hornoch, Peter
中科院分区：
文献类型：
--
作者：
Anderson, Nicholas R.;Ash, Joan S.;Tarczy-Hornoch, Peter
目的：为了探讨如何实施一个全面的新的生物信息学分析系统将影响工作流程，协作和信息管理在一个小的遗传research labor.Design：这是一个纵向的定性研究的七个人参与基因组和蛋白质组学研究。研究数据的收集使用的照明/响应的方法沉浸在环境中。其他定性数据的收集使用非正式的半结构化访谈，参与者观察实验室会议，并直接观察实验室研究人员从事特定tasks. Measures：访谈，观察和现场笔记数据进行编码和分析的基础上，三个分析视角。一个子集的数据进行独立评估的外部researcher，以提高Results. Results的可信度：三个重复出现的主题在研究中观察到。(1)对软件工具的满意度和接受度往往与角色和目标有关。(2)该系统主要被视为一个测量系统，而不是一个“总的实验室分析系统”。(3)实验室会议不再强调该系统，而是更倾向于传统的数据分析技术。这些主题支持的意见，该系统没有被用来充分发挥其潜力，在labor.Conclusion：在这项研究中确定的主题表明，复杂的遗传学研究人员面临类似的问题，在其他领域的专业人员的技术实施。我们建议领导层的支持和持续的培训以及学术课程的发展可以提高生物信息学分析系统更有效地使用的机会。(C)2006爱思唯尔爱尔兰有限公司保留所有权利。
Objective: To explore how the implementation of a comprehensive new bioinformatics analysis system would affect workflow, collaboration and information management in a small genetic research lab.Design: This was a longitudinal qualitative study of seven individuals involved in genomic and proteomic research. The study data were gathered using the illuminative/responsive approach of immersion in the environment. Additional qualitative data were gathered using informal semi-structured interviews, participant observation in lab meetings, and direct observation of lab researchers engaged in specific tasks.Measurements: Interview, observation and field note data were coded and analyzed based on three analysis perspectives. A subset of the data was independently evaluated by an external researcher to enhance the trustworthiness of results.Results: Three reoccurring themes were observed in the study. (1) Satisfaction and acceptance of software tools tended to be role and goal specific. (2) The system was seen primarily as a measurement system rather than a "total laboratory analysis system". (3) Lab meetings deemphasized the system, preferring more traditional data analysis techniques. These themes support the observations that the system was not used to its full potential in the lab.Conclusion: Themes identified in this study suggest that sophisticated genetic researchers face similar problems of technology implementation as do professionals in other fields. We recommend that leadership support and on-going training and evolution of academic curricula can improve chances of bioinformatics analysis systems becoming used more effectively. (C) 2006 Elsevier Ireland Ltd. All rights reserved.