Scientists’ sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support

BMC Bioinformatics

Barbara Mirel²  Carsten Görg¹ 

[1] Computational Bioscience Program, School of Medicine, University of Colorado, Denver, Colorado, USA

[2] School of Education, University of Michigan, Ann Arbor, Michigan 48109, USA

关键词: Case study;    Qualitative research;    Visualization;    Network analysis;    Systems biology;    Cognitive tasks;    Complex workflow;    Usability;    Sense making;   

Others  :  818646
DOI  :  10.1186/1471-2105-15-117

 received in 2012-11-12, accepted in 2014-04-08,  发布年份 2014

【 摘 要 】

A common class of biomedical analysis is to explore expression data from high throughput experiments for the purpose of uncovering functional relationships that can lead to a hypothesis about mechanisms of a disease. We call this analysis expression driven, -omics hypothesizing. In it, scientists use interactive data visualizations and read deeply in the research literature. Little is known, however, about the actual flow of reasoning and behaviors (sense making) that scientists enact in this analysis, end-to-end. Understanding this flow is important because if bioinformatics tools are to be truly useful they must support it. Sense making models of visual analytics in other domains have been developed and used to inform the design of useful and usable tools. We believe they would be helpful in bioinformatics. To characterize the sense making involved in expression-driven, -omics hypothesizing, we conducted an in-depth observational study of one scientist as she engaged in this analysis over six months. From findings, we abstracted a preliminary sense making model. Here we describe its stages and suggest guidelines for developing visualization tools that we derived from this case. A single case cannot be generalized. But we offer our findings, sense making model and case-based tool guidelines as a first step toward increasing interest and further research in the bioinformatics field on scientists’ analytical workflows and their implications for tool design.

【 授权许可】

   
2014 Mirel and Görg; licensee BioMed Central Ltd.

【 图 表 】

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