Abstract
In our previous study, we visualized microarray data of hepatocellular carcinoma (HCC) by using self-organizing-map, and investigated molecular signature representing the development of HCC. In this study, we propose two visualization methods of microarray data with Euclidean distance classifiers and Sammonpsilas nonlinear mapping. Our proposed methods will serve as tool to discover molecular signature representing the development of HCC for molecular biologists or doctors.