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Animated interval scatter-plot views for the exploratory analysis of large scale microarray time-course data.

Craig, Paul; Kennedy, Jessie; Cumming, Andrew

Authors

Paul Craig



Abstract

Microarray technologies are a relatively new development that allow biologists to monitor the activity of thousands of genes (normally around 8,000) in parallel across multiple stages of a biological process. While this new perspective on biological functioning is recognised as having the potential to have a significant impact on the diagnosis, treatment, and prevention of diseases, it is only through effective analysis of the data produced that biologists can begin to unlock this potential. A significant obstacle to achieving effective analysis of microarray time-course is the combined scale and complexity of the data. This inevitably makes it difficult to reveal certain significant patterns in the data. In particular, it is less dominant patterns and, specifically, patterns that occur over smaller intervals of an experiment's overall time-frame that are more difficult to find. While existing techniques are capable of finding either unexpected patterns of activity over the majority of an experiment's time-frame or expected patterns of activity over smaller intervals of the time-frame, there are no techniques, or combination of techniques, that are suitable for finding unsuspected patterns of activity over smaller intervals. In order to overcome this limitation we have developed the Time-series Explorer, which specifically supports biologists in their attempts to reveal these types of pattern by allowing them to control an animated interval scatter-plot view of their data. This paper discusses aspects of the technique that make such an animated overview viable and describes the results of a user evaluation assessing the practical utility of the technique within the wider context of microarray time-series analysis as a whole.

Citation

Craig, P., Kennedy, J., & Cumming, A. (2005). Animated interval scatter-plot views for the exploratory analysis of large scale microarray time-course data. Information Visualization, 4(3), 149-163. https://doi.org/10.1057/palgrave.ivs.9500101

Journal Article Type Article
Online Publication Date Jul 14, 2005
Publication Date 2005-09
Deposit Date May 16, 2008
Publicly Available Date May 16, 2017
Print ISSN 1473-8716
Electronic ISSN 1473-8724
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 4
Issue 3
Pages 149-163
DOI https://doi.org/10.1057/palgrave.ivs.9500101
Keywords Biology; Gene activity; Microarray technology; Data analysis; Pattern recognition; Computer programming; Time Series Explorer program; Animation; Scatter-plot; Evaluation;
Public URL http://researchrepository.napier.ac.uk/id/eprint/1813
Publisher URL http://dx.doi.org/10.1057/palgrave.ivs.9500101
Contract Date May 16, 2017

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