Visualization of gene combinations

Advances in the field of microarray technology have at-tracted a lot of attention in recent years. More and more biological experiments are conducted based on microar-rays. The challenge researchers face today is to analyze and understand the collected data. We present a visual approach to support understanding microarray data. In contrast to other visualization tech-niques, which represent expression of genes, we go one step further and make a switch to combinations of genes. Gene combinations bear more information, and hence, can lead to new hypotheses about the data. However, the increased amount of information imposes several challenges to an interactive visualization approach. We propose analytical and visual methods to deal with these challenges