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Paul Craig (Edinburgh Napier University, Edinburgh, United Kingdom)
The perspective on biological functioning supported by microarray technologies is recognised as having the potential to have a significant impact on the diagnosis, treatment, and prevention of diseases. It is, however, only through effective analysis of the data produced that biologists can begin to unlock this potential. A significant obstacle to achieving effective analysis is the combined scale and complexity of the data. This makes it difficult to reveal certain significant patterns in the data. In particular it is less dominant patterns and, specifically, patterns that occur in a smaller number of samples relating to an interval of time that can be more difficult to find. The Microarray Time-series Explorer (MaTSE) allows users to find these types of pattern by giving them control of an animated scatter-plot visualisation and letting them to interactively explore their data. Our poster describes how the animated scatter-plot can be used to find patterns and how supporting functionality, such as the overlay of gene groupings, pattern storage and multi-condition views, has been applied to enhance the overall usability and effectiveness of the technique.