3D Visualization of Gene Clusters

An essential step in the analysis of gene expression profile data is the detection of gene groups that have similar expression patterns. Although many clustering algorithms have been proposed for such task, problems such as visualizing the clustering results are still not satisfactorily addressed. In this paper, a novel methodology for drawing the gene clusters in 3D is proposed. The algorithm firstly allocates the genes within a cluster to a local area – InfoCube using Force-Directed Placement Spring Model; it then allocates all the InfoCubes within a global area using the same method. The bottom-up approach saves time in coordinates’ computation and successfully avoids the space partition problem in multi-layer graph drawing. It is not only effective in displaying the double-layer clustering results but also can be extended to display other multi-layer graphs with hierarchical relationships.