Fractal views: a fractal-based method for controlling information display
ACM Transactions on Information Systems (TOIS)
H-BLOB: a hierarchical visual clustering method using implicit surfaces
Proceedings of the conference on Visualization '00
Ordered and quantum treemaps: Making effective use of 2D space to display hierarchies
ACM Transactions on Graphics (TOG)
Dynamic Aggregation with Circular Visual Designs
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
Research report: Interacting with huge hierarchies: beyond cone trees
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
Tree-Maps: a space-filling approach to the visualization of hierarchical information structures
VIS '91 Proceedings of the 2nd conference on Visualization '91
Hierarchical Data Visualization Using a Fast Rectangle-Packing Algorithm
IEEE Transactions on Visualization and Computer Graphics
Hierarchical Visualization of Network Intrusion Detection Data
IEEE Computer Graphics and Applications
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In the age of combinatorial chemistry and high throughput screening, large-scale data of bioactive chemicals oriented to drug development are being accumulated. Due to the difficulties inherent in understanding such large quantities of data, information visualization techniques are increasingly attractive. Authors apply "Heiankyo View", which is the technique for the representation of large-scale hierarchical data, for the visualization of multi-dimensional data of bioactive chemicals. In the present study, we investigated applicability of the visualization technique to the structure-activity relationship (SAR) analyses. The study first classifies chemicals according to similarity in their biological actions through self-organizing map analysis. It then applies a recursive partitioning method to find the relationship between biologically based categories and chemical structure, and finally it stores the drugs as hierarchical data. HeiankyoView is suitable for the visualization of such hierarchical data. This paper first describes the algorithmic overview of Heiankyo View, and then provides some example of visualization of multi-dimensional data of bioactive chemicals.