Visualizing set concordance with permutation matrices and fan diagrams

Interacting with Computers

Volumn 19, Issue 5-6, 2007, Pages 630-643

  Kim, Bohyoung ^a   Lee, Bongshin ^b   Seo, Jinwook ^c  

^a Seoul National University Bundang Hospital   (South Korea)

^b MICROSOFT RESEARCH   (United States)

^c CHILDREN'S NATIONAL MEDICAL CENTER   (United States)

Author keywords

Cluster comparison; Fan diagram; Permutation matrix; Set concordance; Venn diagram

Indexed keywords

COMPUTER AIDED SOFTWARE ENGINEERING; ERRORS; INTERACTIVE COMPUTER SYSTEMS; NATURAL SCIENCES COMPUTING; USER INTERFACES;

CLUSTER COMPARISON; CONCORDANCE (OR DISCORDANCE) ANALYSIS; CONSET; FAN DIAGRAMS; INTERACTIVE VISUALIZATION TOOL; PERMUTATION MATRICES; SET CONCORDANCE; STANDARD VENN DIAGRAM;

PROBLEM SOLVING;

EID: 34548479973     PISSN: 09535438     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.intcom.2007.05.004     Document Type: Article

References (25)

1. Abello J., and Korn J. MGV: a system for visualizing massive multigraphs. IEEE Transactions on Visualization and Computer Graphics 8 1 (2002) 21-38
2. Ankerst M., Breunig M.M., Kriegel H.-P., and Sander J. OPTICS: ordering points to identify the clustering structure. ACM SIGMOD Record 28 2 (1999) 49-60
3. Baldonado M., Woodruff A., and Kuchinsky A. Guidelines for using multiple views in information visualization. Proceedings of Advanced Visual Interfaces (2000), Palermo, Italy 110-119
4. Becker R.A., and Cleveland W.S. Brushing scatterplots. Technometrics 29 (1987) 127-142
5. Bertin J. Graphics and Graphic Information-Processing (1981), de Gruyter, Berlin; New York
6. Card S.K., Mackinlay J.D., and Shneiderman B. Readings in Information Visualization: Using Vision to Think (1999), Morgan-Kaufmann, San Francisco, California
7. Davies, C. and Medyckyj-Scott, D., 1994. Introduction: The importance of human factors. In: Hearnshaw, H.M. and Unwin, D. (Eds.), Visualization in geographical information systems, Chichester, New York, pp. 189-192.
8. Eisen, M.B., Spellman, P.T., Brown, P.O., Botstein, D., 1998. Cluster analysis and display of genome-wide expression patterns. In: Proceedings of the National Academy of Sciences of the United States of America 95 (25), 14863-14868.
9. Furnas, G.W., 1986. Generalized fisheye views. In: Proceedings of the Conference on Human Factors in Computing Systems, Boston, MA, USA, pp. 18-23.
10. Ghoniem, M., Jussien, N., and Fekete, J.-D., 2004. VISEXP: visualizing constraint solver dynamics using explanations. In: Proceedings of the Seventh International Florida Artificial Intelligence Research Society Conference, Miami, FL, USA, 2004.
11. Guo D. Coordinating computational and visual approaches for interactive feature selection and multivariate clustering. Information Visualization 2 (2003) 232-246
12. Henry N., and Fekete J.-D. MatrixExplorer: a dual-representation system to explore social networks. IEEE Transactions on Visualization and Computer Graphics 12 5 (2006) 677-684
13. Kestler H.A., Muller A., Gress T.M., and Buchholz M. Generalized Venn Diagrams: a new method of visualizing complex genetic set relations. Bioinformatics 21 8 (2005) 1592-1595
14. Kincaid, R., 2004. VistaClara: an interactive visualization for exploratory analysis of DNA microarrays. In: Proceedings of the ACM Symposium on Applied Computing, Nicosia, Cyprus, 2004, pp. 167-174.
15. Mäkinen E., and Siirtola H. The barycenter heuristic and the reorderable matrix. Informatica 29 3 (2005) 357-363
16. Munzner T., Guimbretiere F., Tasiran S., Zhang L., and Zhou Y. TreeJuxtaposer: scalable tree comparison using Focus+Context with guaranteed visibility. ACM Transactions on Graphics 22 3 (2003) 453-462
17. Seo J., Gordish-Dressman H., and Hoffman E.P. An interactive power analysis tool for microarray hypothesis testing and generation. Bioinformatics 22 7 (2006) 808-814
18. Seo J., and Shneiderman B. Interactively exploring hierarchical clustering results. Computer 35 7 (2002) 80-86
19. Seo J., and Shneiderman B. A rank-by-feature framework for interactive exploration of multidimensional data. Information Visualization 4 2 (2005) 99-113
20. Shneiderman, B., 1996. The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of IEEE Symposium on Visual Languages, Boulder, CO, USA, 1996, pp. 336-343.
21. Spoerri, A., 1993. InfoCrystal: a visual tool for information retrieval. In: Proceedings of the IEEE Visualization Conference, San Jose, CA, USA, pp. 150-157.
22. Spoerri, A., 2004. MetaCrystal: Visualizing the degree of overlap between search engines. In: Proceedings of the ACM International World Wide Web Conference, New York, NY, USA, pp. 378-379.
23. van Ham, F., 2003. Using multilevel call matrices in large software projects. In: Proceedings of IEEE Symposium on Information Visualization, Seattle, WA, USA, pp. 227-232.
24. Verroust A., and Viaud M.-L. Ensuring the drawability of extended euler diagrams for up to 8 sets. Lecture Notes in Computer Science 2980 (2004) 128-141
25. Zeeberg B., Feng W., Wang G., Wang M., Fojo A., Sunshine M., Narasimhan S., Kane D., Reinhold W., Lababidi S., Bussey K., Riss J., Barrett J., and Weinstein J. GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biology 4 4 (2003) R28