Abstract
One important purpose of conducting gene expression experiments is to understand the correlation of gene expression profiles to disease states. Based on the notion of emerging patterns and an entropy-oriented discretization method, we discover groups of genes that are correlated to disease states in a significant way. In each group, every member gene constrained by a specific expression interval, unanimously occurs only in one type of cells with a maximally large frequency, but never unanimously happens in the other types of cells. According to our studies on the colon tumor dataset, such gene groups (also called patterns) can reach a frequency of 90%, providing good insight into the correlation of gene expression profiles to disease states. The patterns can be used to correctly predict whether a new cell is normal or cancerous.
