Visual information seeking: tight coupling of dynamic query filters with starfield displays
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
UIST '94 Proceedings of the 7th annual ACM symposium on User interface software and technology
Metadata visualization for digital libraries: interactive timeline editing and review
Proceedings of the third ACM conference on Digital libraries
Hierarchical parallel coordinates for exploration of large datasets
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Introduction to Time Series Analysis and Forecasting: With Applications of SAS and SPSS
Introduction to Time Series Analysis and Forecasting: With Applications of SAS and SPSS
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Angular Brushing of Extended Parallel Coordinates
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Information Visualization - Special issue: Bioinformatics visualization
Nature-inspired visualisation of similarity and relationships in human systems and behaviours
Information Visualization - Special issue on visual analysis of human dynamics
Dimensionality reduction oriented toward the feature visualization for ischemia detection
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
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Microarrays are a relatively new, high-throughput data acquisition technology for investigating biological phenomena at the microlevel. One of the more common procedures for microarray experimentation is that of the microarray time-course experiment. The product of microarray time-course experiments is time-series data, which subject to proper analysis has the potential to have significant impact on the diagnosis, treatment, and prevention of diseases. While existing information visualization techniques go some way to making microarray time-series data more manageable, requirements analysis has revealed significant limitations. The main finding was that users were unable to uncover and quantify common changes in value over a specified time-period. This paper describes a novel technique that provides this functionality by allowing the user to visually formulate and modify measurable queries with separate time-period and condition components. These visual queries are supported by the combination of a traditional value against time graph representation of the data with a complementary scatter-plot representation of a specified time-period. The multiple views of the visualization are coordinated so that the user can formulate and modify queries with rapid reversible display of query results in the traditional value against time graph format.