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

ABSTRACT: 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 helpfu

SUBMITTER: Mirel B 

PROVIDER: S-EPMC4021544 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature