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

Information Visualization

Volumn 4, Issue 3, 2005, Pages 149-163

  Craig, Paul ^a   Kennedy, Jessie ^a   Cumming, Andrew ^a  

^a EDINBURGH NAPIER UNIVERSITY   (United Kingdom)

Author keywords

animation; Bioinformatics; evaluation; microarray; time series

Indexed keywords

EID: 84993741804     PISSN: 14738716     EISSN: 14738724     Source Type: Journal    
DOI: 10.1057/palgrave.ivs.9500101     Document Type: Article

References (29)

1. Schena M, Shalon D, Davis RW, Brown PO. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995; 270: 467–470.
2. Schena M, Shalon D, Heller R, Chai A, Brown PO, Davis RW. Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes. Proceedings of the National Academy of Sciences of the United States of America 1996; 93: 10614–10619.
3. Duggan DJ, Bittner M, Chen Y, Meltzer P, Trent J. Expression profiling using cDNA microarrays. Nature Genetics 1999; 21: 10–14.
4. Stein T, Morris J, Davies C, Weber-Hall S, Duffy M-A, Heath V, Bell A, Ferrier R, Sandilands G, Gusterson B. Involution of the mouse mammary gland is associated with an immune cascade and an acute-phase response, involving LBP, CD14 and STAT3. Breast Cancer Research 2004; 6: R75–R91.
5. Hughes TR, Marton MJ, Jones AR, Roberts CJ, Stoughton R, Armour CD, Bennett HA, Coffey E, Dai H, He YD. Functional discovery via a compendium of expression profiles. Cell 2002; 102: 109–126.
6. Wen X, Fuhrman S, Michaels GS, Carr DB, Smith S, Barker JL, Somogyi R. Large-scale temporal gene expression mapping of central nervous system development. Proceedings of the National Academy of Sciences of the United States of America 1998; 95: 334–339.
7. Brown PO, Botstein D. Exploring the new world of the genome with DNA microarrays. Nature Genetics 1999; 21: 33–37.
8. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America 1998; 95: 14863–14868.
9. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander E, Golub T. Interpreting patterns of gene expression with self-organizing maps. Proceedings of the National Academy of Sciences of the United States of America 1999; 96: 2907–2912.
10. Raychaudhuri S, Stuart JM, Altman RB. Principal components analysis to summarize microarray experiments: Application to sporulation time series. Pacific Symposium on Biocomputing 2000; 452–463.
11. Shneiderman B. The eyes have it: A task by data type taxonomy for information visualizations. Proceedings of the IEEE Visual Languages 1996; 336–343.
12. Segal E, Taskar B, Gasch A, Friedman N, Koller D. Rich probabilistic models for gene expression. Bioinformatics 2001; 17: 243–252.
13. Hochheiser H, Shneiderman B. Dynamic query tools for time series data sets: Timebox widgets for interactive exploration. Information Visualisation 2004; 3: 1–18.
14. Seo J, Shneiderman B. Interactively exploring hierarchical clustering results. IEEE Computer 2002; 35: 80–86.
15. Craig P, Kennedy JB, Cumming A. Towards visualising temporal features in large scale microarray time-series data. International Conference on Information Visualisation – IV2002 2002 (University of London, London, GB), IEEE Press: New York, 2002.
16. Craig P, Kennedy JB. Coordinated Graph and Scatter-Plot Views for the Visual Exploration of Microarray Time-Series Data. J 2003 IEEE Symposium on Information Visualization. 2003 (Seattle WA), IEEE Computer Society: Silver Spring, MD, 2003.
17. Nakakoji K, Takashima A, Yamamoto Y. Cognitive effects of animated visualization in exploratory visual data analysis. Information Visualisation 2001 (Los Alamos CA), IEEE Computer Society: Silver Spring, MD, 2001; 77–84.
18. Bartram L. Perceptual and Interpretative Properties of Motion for Information Visualization. School of Computing Science, Simon Fraser University, 1997.
19. GeneSpring. 2004 Silicon Genetics. http://www.silicongenetics.com.
20. Nadon R, Shoemaker J. Statistical issues with microarrays: Processing and analysis. TRENDS in Genetics 2002; 18: 265–271.
21. Quackenbush J. Computational Analysis of Microarray Data. Nature Reviews Genetics 2001; 2: 418–427.
22. Weisstein EW. ‘Statistical Median.’ From MathWorld – A Wolfram Web Resource http://mathworld.wolfram.com/StatisticalMedian.html, 2005.
23. Fekete J, Plaisant C. Interactive information visualization of a million items. IEEE Symposium on Information Visualization 2002 (Boston, MA, USA), IEEE Computer Society: Silver Spring, MD, 2002; 117–126.
24. Colby G, Scholl L. Transparency and blur as selective cues for complex visual information. SPIE Image Handling and Reproduction Systems Integration. 1991 (San Jose, CA, USA), Bellingham, WA, SPIE, 1991; 114–125.
25. Buja A, McDonald JA, Michalak J, Stuetzle W. Interactive Data Visualization Using Focusing and Linking. IEEE Visualization 1991. (San Diego, CA, USA), IEEE Computer Society Press: Silver Spring, MD, 1991; 156–163.
26. Shneiderman B. Dynamic Queries for Visual Information Seeking. IEEE Software 1994; 11: 70–77.
27. Eick SG. Data Visualization Sliders. UIST 1994. (Marina del Ray, CA, USA), ACM Press: New York, 1994; 119–120.
28. Fekete J, Plaisant C. Excentric Labeling: Dynamic Neighborhood Labeling for Data Visualization. Conference on Human Factors in Computing Systems 1999 (Pittsburgh, Pennsylvania, USA). ACM Press New York, NY, 1999; 512–519.
29. Saraiya P, North C, Duca K. An Evaluation of Microarray Visualization Tools for Biological Insight. IEEE Symposium on Information Visualization (INFOVIS’ 04). (Austin, TX), 2004; 1–8.