Graphical exploratory data analysis
Graphical exploratory data analysis
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
InfoCrystal: a visual tool for information retrieval & management
CIKM '93 Proceedings of the second international conference on Information and knowledge management
Visualization tools for self-organizing maps
Proceedings of the fourth ACM conference on Digital libraries
Using shape to visualize multivariate data
Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management
Self-Organizing Maps
Information Rich Glyphs for Software Management Data
IEEE Computer Graphics and Applications
Finding predictive gene groups from microarray data
Journal of Multivariate Analysis
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
Data analysis in modern biomedical research has to integrate data from different sources, like microarray, clinical and categorical data, so called multi-modal data. The reef SOM, a metaphoric display, is applied and further improved such that it allows the simultaneous display of biomedical multi-modal data for an exploratory analysis. Visualizations of microarray, clinical, and category data are combined in one informative and entertaining image. The U-matrix of the SOM trained on microarray data is visualized as an underwater sea bed using color and texture. The clinical data and category data are integrated in the form of fish shaped glyphs. The resulting images are intuitive, entertaining and can easily be interpreted by the biomedical collaborator, since specific knowledge about the SOM algorithm is not required. Visual inspection enables the detection of interesting structural patterns in the multi-modal data when browsing through and zooming into the image. Results of such an analysis are presented for the van't Veer data set.