Analysis of cellular pathways and networks in terms of logic relations is important to decipher the networks of molecular interactions that underlie cellular function. A computational approach for identifying lower and higher order gene logic associations was presented on the base of graph coloring theory and applied it to the colon cancer mRNA microarray data. Then the logic relationships of 51 oncogenes and cancer suppressor genes are analyzed and the logic association network of them was constructed. The signal pathway of TGFβ from the network model was found and verified by the colon cancer pathway of KEGG. The model reveals many higher order logic relationships of cancer genes. These relationships illustrate the complexities that arise in cancer cellular networks because of interacting pathways. The results show that this method is feasible and is expected to give a reference to the medical molecular biologist.