A dramatic increase in the amount of genomic expression data with knowledge in to mine for getting a principal understanding of “what is a considered disease at the genomic level” is available today. We give a short overview about common processing of micro array expression data. Furthermore we introduce a complex bioinformatic approach combining properly several analyzing methods to mine gene expression data and biomedical literature. Gene patterns and gene relation information as results from data and text mining is to be considered as integral part for modeling genetic networks. We apply methods of case-based-reasoning for generating a similarity tree consisting of genetic networks. These networks are efficient facilities to understand the dynamic of pathogenic processes and to answer a question like “what is a disease x in the genomic sense”?